Borrowing it
Nothing to install: this file belongs to EndogenAI/dogma. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/EndogenAI/dogma/main/.github/skills/corpus-sweep/SKILL.mdgit clone --depth 1 https://github.com/EndogenAI/dogmaWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/endogenai/dogma/corpus-sweep)<a href="https://agentmods.dev/skills/endogenai/dogma/corpus-sweep"><img src="https://agentmods.dev/badge/skills/endogenai/dogma/corpus-sweep/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/endogenai/dogma/corpus-sweep"><img src="https://agentmods.dev/badge/skills/endogenai/dogma/corpus-sweep.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00078 | $0.01073 |
| Opus 5.5 | $0.00031 | $0.00429 |
| Sonnet 5.5 | $0.00016 | $0.00215 |
| Haiku 4.5 | $0.00008 | $0.00107 |
Grade A, and why
corpus-sweep scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Corpus Sweep
Governing Axiom
This skill enacts the Endogenous-First axiom from MANIFESTO.md and is governed by AGENTS.md § Programmatic-First Principle. Before sweeping any corpus, check whether a prior sweep result is already cached in .cache/sources/ or recorded in the active session scratchpad — re-sweeping a cached corpus wastes tokens and violates Local Compute-First.
"Scaffold from existing system knowledge and external best practices." — MANIFESTO.md § 1 Endogenous-First
When to Use
- A synthesis or implementation phase requires patterns found across ≥20 source documents.
- The Orchestrator needs a cross-cutting summary before delegating to a Synthesizer.
- A research epic requires an initial landscape report before forming hypotheses.
- You are auditing agent files, research docs, or session scratchpads for a recurring pattern.
Do not use this skill for:
- Single-document reads (use
read_filedirectly). - Live web fetches (use the
source-cachingskill instead). - Tasks where the required context fits within a single
grep_searchorsemantic_searchcall.
Workflow
-
Pre-warm cache — before reading any source file, run:
uv run python scripts/fetch_all_sources.pySkip if
.cache/sources/manifest.jsonwas updated within the current session. -
Read source index — identify the target corpus:
- For research sources: read
.cache/sources/manifest.jsonto list all cached URLs. - For internal docs: list
docs/research/,docs/guides/, or.github/agents/as appropriate. - Record the total document count before batching.
- For research sources: read
-
Batch-read docs — divide the corpus into batches of 5–10 files. For each batch:
- Use
read_file(for long docs) orgrep_search(for keyword scanning). - Record findings per document: filename, key claim, relevant quote (≤50 words), and cross-references noted.
- Stop scanning a document once sufficient signal is found — avoid reading full content when a heading scan suffices.
- Use
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 120 lines · 78 tokens per session scan A 55451dc085df
corpus-sweep is a skill published in the GitHub repository EndogenAI/dogma (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 78 tokens to every session and 1,073 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
corpus-sweep compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| corpus-sweepEndogenAI/dogma | Skill | 2 | 2mo ago | Apache-2.0 | A | 78 | Claude Code |
| custom-brand-designKbWen/agentic-os | Skill | 227 | 4d ago | MIT | A | 23 | Claude Code, Codex |
| air-blackbox-sales-agentairblackbox/airblackbox | Skill | 25 | 4d ago | Apache-2.0 | A | 248 | Claude Code, Codex |
| interpret-resultsairblackbox/airblackbox | Skill | 25 | 4d ago | Apache-2.0 | A | 49 | Claude Code |
| compliance-scanairblackbox/airblackbox | Skill | 25 | 4d ago | Apache-2.0 | A | 51 | Claude Code |
| nio-external-scorecore0-io/nio | Skill | 20 | 13d ago | Apache-2.0 | A | 97 | Claude Code |
| nio-scancore0-io/nio | Skill | 20 | 13d ago | Apache-2.0 | A | 81 | Claude Code |