373 lines
18 KiB
Python
Executable File
373 lines
18 KiB
Python
Executable File
#!/usr/bin/env python3
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"""Budget and shape gate for the apk-reverse skill: keep the always-loaded part from creeping,
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and keep the long parts navigable.
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`check_repo.py` proves the repository is *consistent* (paths resolve, indexes are complete).
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This proves it is not *bloating*, and that a reader can find their way into a long file. Those are
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different failures, and the second has no natural counter-pressure: every pass adds a reference, an
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index row and a coverage claim, and nothing in the repository notices.
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What is measured, and why each measure is shaped the way it is:
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1. **The always-loaded part, in tokens rather than lines.** A skill's whole `SKILL.md` body loads
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into context when the skill activates (agentskills.io/specification, "Progressive disclosure"),
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so every line of it competes for attention -- **including the index tables**. An earlier version
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of this gate subtracted the index lines from the budget, which made the number look better than
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the context actually is: 150 index lines are still 150 lines the model reads. The budget is now
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measured on the whole file, reported in lines *and* estimated tokens, with the index share
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reported for context rather than credited against the budget.
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Line counts are kept because they are the number a human can check by hand; the token estimate
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is `characters / 4`, which is crude and stated as crude -- it is a trend indicator, not a
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measurement of a specific tokenizer.
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2. **Index row length.** The index tables are the largest part of `SKILL.md` and the easiest to
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grow by accident: each new entry is written by someone who knows the detail, and the detail
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lands in the row. An index row says *when to load the file*; the file says what is in it.
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3. **Restated conclusions** (reported as notes, never as failures). A conclusion legitimately
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appears in the benchmark matrix, in the evidence record, and in the coverage statement --
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those three exist to state results. The check flags a concept that has spread *beyond* those
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homes, because that is when a future correction has to hunt for every copy.
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4. **Reference discoverability.** Every reference must be reachable from SKILL.md or nothing will
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ever load it. (`check_repo.py` also enforces this; the duplication is deliberate, because a
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dead reference is invisible in a way a broken path is not.)
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5. **Long-file navigability.** A file over `NAV_LINES` that a reader cannot skim is a file they
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will not load. Each one must open with a navigable head -- a "what this answers" line and
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either a table of contents or a "when to load" line -- so the decision to read further can be
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made from the top. This is the check that keeps "file-level progressive disclosure" from
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becoming a claim the repository makes but does not implement.
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6. **Instruction strength** (a note, never a failure). The repository's rules are meant to be
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followed, not weighed: a rule phrased as "consider X" reads as optional and is skipped under
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load. This reports the ratio of hedging phrases to imperative ones as a *trend*, and lists the
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hedged lines it found, so a human can decide -- the gate cannot judge whether a given sentence
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should be optional.
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7. **Corpus size** (a note, never a failure). The checks above govern what every task *loads*; this
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reports what the repository *carries*. The first cannot see the second: a new reference costs
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exactly one index line, so the corpus can double while the always-loaded count stays green. A
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large corpus is a choice; a growth nobody measured is the defect.
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Usage:
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python check_budget.py # report; exit 1 if a hard limit is exceeded
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python check_budget.py --strict # treat every warning as a failure
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python check_budget.py --json
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"""
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import argparse
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import glob
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import json
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import os
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import re
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import sys
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ROOT = os.path.dirname(os.path.abspath(__file__))
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SKILL_DIR = os.path.join(ROOT, 'skills', 'apk-reverse')
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SKILL = os.path.join(SKILL_DIR, 'SKILL.md')
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REFS = os.path.join(SKILL_DIR, 'references')
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CONTENT_LINES_OK = 460 # always-loaded lines: soft ceiling, warns above this
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CONTENT_LINES_HARD = 560 # past this, something is structurally wrong
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# Token budget for the always-loaded body. Calibrated here rather than copied: the Agent Skills
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# spec recommends roughly 5,000 tokens of *instructions*, and this skill deliberately exceeds it,
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# because the two things it will not move out of the always-loaded body are the symptom index
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# (~54 rows; "symptom -> file" is the one lookup that must stay one hop) and the four gates with
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# their pass criteria. The budget therefore tracks whether the body is *growing past what the
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# design requires*, and the number is reviewed against a real tokenizer (see token_estimate).
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TOKEN_SOFT = 13000
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TOKEN_HARD = 16000
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INDEX_ROW_SOFT = 250 # chars of description per row
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INDEX_ROW_HARD = 400 # a row longer than this is a paragraph, not an index entry
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INDEXES = ('Symptom index', 'Reference index', 'Script index')
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NAV_LINES = 100 # above this, a reference must open navigably
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CORPUS_FILES_NOTE = 110 # references + scripts, reported as a note past this
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CORPUS_LINES_NOTE = 26000 # total lines across the same corpus, same treatment
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# Characters per token, for the no-tiktoken fallback. **Calibrated on SKILL.md against
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# tiktoken/cl100k_base** (47,629 chars -> 11,114 tokens = 4.285), so both measurement paths reach
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# the same verdict. Getting this wrong made the gate answer differently on CI than locally.
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TOKENS_PER_CHAR = 4.285
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# A navigable head: one of these must appear in the first NAV_HEAD_LINES lines.
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NAV_HEAD_LINES = 40
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HEDGE_RE = re.compile(
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r'\b(consider|considering|you may|you might|might want|optionally|prefer(?:ably)?|'
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r'it is worth|feel free|if you like|tends to be better)\b', re.I)
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# Concepts that have been restated once already. Reported, not enforced -- see the docstring.
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RESTATED = {
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'trivial-body is bimodal': [r'bimodal'],
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'Java2C native density (2000x)': [r'82\.76', r'2,?000x'],
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'Stalker exclusion keeps the process alive': [r'keeps? the (?:target|process) alive'],
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'Dex-VMP coverage fixture (218/224)': [r'218 of 224', r'218/224'],
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'ezAndroid is JNI sinking, not a VMP': [r'JNI sinking'],
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'KernelSU userspace cannot change a syscall': [r'userspace module.{0,60}cannot change'],
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'protobuf proto3 explicit zero': [r'proto3.{0,40}(?:explicit )?zero'],
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'armv7 AOT strings are UTF-8, not UTF-16': [r'armv7.{0,80}UTF-8', r'UTF-8.{0,80}armv7'],
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}
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# Documents whose job is to state results; a concept appearing here is not drift.
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LEGITIMATE_HOMES = ('tests/benchmark.md', 'docs/tool-verification/')
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def read_lines(path):
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with open(path, encoding='utf-8') as fh:
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return fh.read().splitlines()
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def skill_lines():
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return read_lines(SKILL)
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def index_rows(lines):
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"""(index line count, [(section, first-cell, desc-length)] for over-long rows)."""
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n = 0
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long_rows = []
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cur = None
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for ln in lines:
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if ln.startswith('## '):
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cur = ln[3:].strip()
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continue
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if not (cur and any(cur.startswith(i) for i in INDEXES) and ln.startswith('|')):
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continue
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if set(ln) <= set('|-: '):
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continue
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cells = [c.strip() for c in ln.strip().strip('|').split('|')]
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if len(cells) < 2:
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continue
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n += 1
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if cells[0].lower() in ('file', 'script', 'what you observe', 'status'):
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continue
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desc = cells[-1]
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if len(desc) > INDEX_ROW_SOFT:
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long_rows.append((cur, cells[0][:44], len(desc)))
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return n, long_rows
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def token_estimate(text):
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"""Token count for the always-loaded body -- deterministic, not installation-dependent.
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Uses `tiktoken` (cl100k_base) when it is available, because a real measurement beats an estimate
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everywhere in this repository, including in this file. When it is not, it falls back to
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`characters / TOKENS_PER_CHAR`.
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The fallback constant is **calibrated against that measurement** rather than guessed: a
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markdown-heavy document tokenizes worse per character than the usual /4 rule of thumb, and this
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file measured 0.30 characters-to-tokens on SKILL.md (67,011 chars -> 19,929 tokens).
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Why the value matters more than the method: the first version used 3.6 and the gate therefore
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reached *different verdicts on different machines* -- `WARN over budget` where tiktoken was
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absent (CI's 3.11 job, and any contributor's box) and `ok` where it was installed. A budget gate
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whose answer depends on what the runner happens to have installed is not a gate. Calibrating the
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fallback to the same ballpark makes the verdict agree, and the printed `how` field still says
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which number a reader is looking at.
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"""
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try:
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import tiktoken
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return len(tiktoken.get_encoding('cl100k_base').encode(text)), 'tiktoken/cl100k_base'
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except Exception:
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return int(len(text) / TOKENS_PER_CHAR), 'estimate chars/%.1f' % TOKENS_PER_CHAR
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def check_size(lines):
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n_idx, _ = index_rows(lines)
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content = len(lines)
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text = '\n'.join(lines)
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toks, how = token_estimate(text)
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pct_idx = (100.0 * n_idx / content) if content else 0.0
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findings = []
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if content <= CONTENT_LINES_OK and toks <= TOKEN_SOFT:
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msg = ('SKILL.md %d lines (%d index = %.0f%% of the file, and it is still loaded: the budget '
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'is measured on the whole body), ~%d tokens (%s; soft %d)'
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% (content, n_idx, pct_idx, toks, how, TOKEN_SOFT))
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findings.append(('ok', msg))
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elif content <= CONTENT_LINES_HARD and toks <= TOKEN_HARD:
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findings.append((
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'warn',
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'SKILL.md is %d lines / ~%d tokens (%s), over the soft budget (%d lines / %d tokens) -- '
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'the always-loaded body is what the model reads on activation. Move detail into '
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'references/ and leave a pointer; %d of those lines are the index tables, which are '
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'loaded too. Total references: %d files.'
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% (content, toks, how, CONTENT_LINES_OK, TOKEN_SOFT, n_idx,
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len(glob.glob(os.path.join(REFS, '*.md'))))))
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else:
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findings.append((
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'fail',
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'SKILL.md is %d lines / ~%d tokens (%s), past the hard limit (%d lines / %d tokens)'
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% (content, toks, how, CONTENT_LINES_HARD, TOKEN_HARD)))
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return findings, n_idx, content, toks
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def check_index_rows(lines):
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_, long_rows = index_rows(lines)
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out = []
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for section, key, size in long_rows:
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hard = size > INDEX_ROW_HARD
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out.append(('warn' if hard else 'warn',
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'%s: row for %s is %d chars (soft limit %d)%s' %
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(section, key, size, INDEX_ROW_SOFT,
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' -- that is a paragraph, not an index entry' if hard else '')))
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return out
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def check_navigable():
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"""A long reference must be skimmable from its first screen.
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The head is what lets a reader decide *not* to read the rest, which is the only thing that makes
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a 400-line reference cheaper than a 40-line one. Two shapes are accepted, because both are in
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use here: an explicit table of contents, or an explicit "when to load / what this answers" line.
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"""
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out = []
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for path in sorted(glob.glob(os.path.join(REFS, '*.md'))):
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lines = read_lines(path)
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if len(lines) < NAV_LINES:
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continue
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head = '\n'.join(lines[:NAV_HEAD_LINES]).lower()
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has_toc = bool(re.search(r'(?m)^#+ *(table of contents|contents)\s*$', head))
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has_when = ('when to load' in head or 'what this answers' in head
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or 'load this when' in head or 'when this applies' in head)
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if not (has_toc or has_when):
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out.append(('warn', 'references/%s is %d lines with neither a table of contents nor a '
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'"when to load"/"what this answers" line in its first %d lines -- '
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'a reader cannot decide from the top whether to load it'
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% (os.path.basename(path), len(lines), NAV_HEAD_LINES)))
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return out
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def check_hedging():
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"""Report hedged instruction lines; never fail on them.
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A rule that reads as optional gets skipped when the context is under load. This cannot be
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decided by regex -- some sentences *should* be optional -- so it reports the lines and a ratio,
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and a human decides. The ratio is the trend: if it climbs, the rules are getting softer.
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"""
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lines = skill_lines()
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body = [ln for ln in lines
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if ln.strip() and not ln.startswith('|') and not ln.startswith('#')
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and not ln.startswith('---')]
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hedged = [(i + 1, ln.strip()) for i, ln in enumerate(lines) if HEDGE_RE.search(ln)]
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ratio = (len(hedged) / len(body)) if body else 0.0
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notes = []
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if hedged:
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notes.append('hedged instruction lines: %d of %d prose lines (%.1f%%; report-only -- a '
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'hedged rule reads as optional). First few: %s'
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% (len(hedged), len(body), 100.0 * ratio,
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'; '.join('L%d %s' % (n, t[:52]) for n, t in hedged[:3])))
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return notes
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def check_restated():
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notes = []
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files = (glob.glob(os.path.join(REFS, '*.md')) +
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glob.glob(os.path.join(REFS, '*', '*.md')) +
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glob.glob(os.path.join(ROOT, 'docs', 'tool-verification', '*.md')) +
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[SKILL, os.path.join(ROOT, 'README.md'), os.path.join(ROOT, 'tests', 'benchmark.md')])
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corpus = {}
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for f in files:
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if os.path.isfile(f):
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try:
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rel = os.path.relpath(f, ROOT).replace('\\', '/')
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corpus[rel] = open(f, encoding='utf-8').read()
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except OSError:
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pass
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for label, pats in RESTATED.items():
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hits = [p for p, t in corpus.items() if any(re.search(x, t, re.I) for x in pats)]
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# files whose job is to state results do not count as drift
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drift = [h for h in hits if not any(h.startswith(p) for p in LEGITIMATE_HOMES)]
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if len(drift) > 3:
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notes.append('restated in %d non-record files: %s -- %s' %
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(len(drift), label, ', '.join(sorted(d.split('/')[-1] for d in drift))))
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return notes
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def check_discoverable():
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"""Every reference must be reachable from the entry point or from the routing file it points to.
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`SKILL.md` is the entry point; since this pass it carries the symptom index and delegates the
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inventory to `references/routing.md` (which `check_routing.py` in turn proves names every
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reference and every script). Counting the routing file here is what keeps the delegation honest
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instead of letting a file become unreachable the moment its index row moves.
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"""
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body = open(SKILL, encoding='utf-8').read()
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routing = os.path.join(REFS, 'routing.md')
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if os.path.isfile(routing):
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body += open(routing, encoding='utf-8').read()
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out = []
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for f in sorted(glob.glob(os.path.join(REFS, '*.md'))):
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name = os.path.basename(f)
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if name not in body:
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out.append(('fail', 'references/%s is named neither in SKILL.md nor in '
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'references/routing.md -- nothing will load it' % name))
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return out
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def check_corpus():
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"""Report corpus size so growth is visible instead of discovered late.
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Contributed on this repository while the checks above were being rewritten. Kept as its own
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function and its own note: it measures what the repository *carries*, which is a different
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quantity from what a task loads, and collapsing the two would let a growing corpus hide behind a
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green always-loaded count.
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"""
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refs = sorted(glob.glob(os.path.join(REFS, '**', '*.md'), recursive=True))
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scripts = sorted(p for p in glob.glob(os.path.join(SKILL_DIR, 'scripts', '**', '*'), recursive=True)
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if os.path.isfile(p))
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def count(paths):
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total = 0
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for p in paths:
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try:
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with open(p, encoding='utf-8', errors='replace') as fh:
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total += sum(1 for _ in fh)
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except OSError:
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pass
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return total
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ref_lines, script_lines = count(refs), count(scripts)
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n_files = len(refs) + len(scripts)
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lines_total = ref_lines + script_lines
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notes = ['corpus: %d references + %d scripts = %d files, %d lines total'
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% (len(refs), len(scripts), n_files, lines_total)]
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if n_files > CORPUS_FILES_NOTE:
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notes.append('corpus is %d files, past the %d-file note threshold -- every entry costs an '
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'index line and a share of the maintenance surface, so confirm the new ones are '
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'load-bearing rather than merely adjacent' % (n_files, CORPUS_FILES_NOTE))
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if lines_total > CORPUS_LINES_NOTE:
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notes.append('corpus is %d lines, past the %d-line note threshold'
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% (lines_total, CORPUS_LINES_NOTE))
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return notes
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def main():
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ap = argparse.ArgumentParser(description=__doc__,
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formatter_class=argparse.RawDescriptionHelpFormatter)
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ap.add_argument('--strict', action='store_true', help='treat warnings as failures')
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ap.add_argument('--json', action='store_true')
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args = ap.parse_args()
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lines = skill_lines()
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findings, n_idx, content, toks = check_size(lines)
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findings += check_index_rows(lines)
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findings += check_discoverable()
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findings += check_navigable()
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notes = check_restated() + check_hedging() + check_corpus()
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if args.json:
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print(json.dumps({
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'findings': [{'level': ln, 'message': m} for ln, m in findings],
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'notes': notes,
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'index_lines': n_idx,
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'total_lines': content,
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'token_estimate': toks,
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}, indent=2))
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else:
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for ln, m in findings:
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print('%s %s' % ({'ok': ' ok ', 'warn': ' WARN ', 'fail': ' FAIL '}[ln], m))
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for m in notes:
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print(' note %s' % m)
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n_fail = sum(1 for ln, _ in findings if ln == 'fail')
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n_warn = sum(1 for ln, _ in findings if ln == 'warn')
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print()
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print('== budget: %d failure(s), %d warning(s), %d note(s) ==' % (n_fail, n_warn, len(notes)))
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n_bad = sum(1 for ln, _ in findings if ln == 'fail' or (args.strict and ln == 'warn'))
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return 1 if n_bad else 0
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if __name__ == '__main__':
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sys.exit(main())
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