autowiki-chunk — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited autowiki-chunk (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Split a document into chunks the agent can process without context overflow. Pick strategy by file type, then read one chunk at a time.
| Extension | Strategy | How to split |
|---|---|---|
.md, .txt | prose | Split at ## or # headers. Fallback: paragraph boundaries (double newline). Target 1K-3K tokens per chunk. |
.log, .jsonl | log | Three sections: head (first 50 lines for format), middle (100 lines from center for patterns), tail (last 100 lines for recency). |
.csv, .tsv | data | Schema (header row) + sample (20 evenly-spaced rows). |
.py, .js, .go | code | Split at def , class , async def . Keep imports and file-level config with first chunk. |
Read the file. Find section headers (## Title or # Title). Split so each chunk is 1K-3K tokens. If no headers, split at paragraph boundaries (blank lines). Avoid splitting mid-paragraph.
To read a specific chunk without loading the full file:
read_file <file> offset=<N> limit=<M>Skip boilerplate: license headers, table of contents, navigation blocks.
Read first 50 lines for format identification (head). Sample 100 lines from the middle third of the file (patterns). Read last 100 lines (recent events). Skip the rest.
For JSONL: the head section surfaces the schema. Middle sections find error signatures and outliers. Tail shows most recent events.
Read the header row for schema. Sample 20 rows evenly distributed through the file. step = max(1, total_rows // 20). Skip the rest.
Schema + 20 rows is ~500 tokens. Full 10K-row CSV is ~100K tokens. Same extraction quality for structural understanding.
Split at top-level function and class boundaries. import statements, file-level constants, and docstrings stay with the first chunk.
Implementation-only functions (getters, I/O helpers) that contain no novel logic or concepts can be summarized in one line rather than processed in full. Focus extraction on: novel algorithms, data structures, configuration that defines system behavior.
offset and limit~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.