dogma: Skill for Claude Code

.github/skills/corpus-sweep/SKILL.md

corpus-sweep is a skill for Claude Code from EndogenAI/dogma. It costs 78 tokens per session (1,073 once invoked), scanned A, original, Apache-2.0.

A process for scanning at least 20 research papers, documents, or agent files in batches to find patterns and produce a short findings summary.

In plain words
What is it for?
Use it to compare many existing documents, inspect a research folder, or find recurring patterns across an agent fleet before synthesis.
Why use it?
It reduces the effort of reading a large collection when you need an overview before making a decision or combining findings.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: mentions AGENTS.md.

This is EndogenAI/dogma's own configuration. It tells Claude Code how to work on dogma itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything dogma configures →

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is uv run python scripts/fetch_all_sources.py.

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/EndogenAI/dogma/main/.github/skills/corpus-sweep/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/EndogenAI/dogma

Made for: Claude Code.

Wrote 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.

agentmods badge for corpus-sweep

README.md
[![agentmods](https://agentmods.dev/badge/skills/endogenai/dogma/corpus-sweep/github.svg)](https://agentmods.dev/skills/endogenai/dogma/corpus-sweep)
Your own site
<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.

agentmods 80×15 button for corpus-sweep

Your own site · 80×15
<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>
Per session 78 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,073 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 2mo ago against content hash 55451dc085df, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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.

.github/skills/corpus-sweep/SKILL.md · 120 lines

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_file directly).
  • Live web fetches (use the source-caching skill instead).
  • Tasks where the required context fits within a single grep_search or semantic_search call.

Workflow

  1. Pre-warm cache — before reading any source file, run:

    uv run python scripts/fetch_all_sources.py
    

    Skip if .cache/sources/manifest.json was updated within the current session.

  2. Read source index — identify the target corpus:

    • For research sources: read .cache/sources/manifest.json to list all cached URLs.
    • For internal docs: list docs/research/, docs/guides/, or .github/agents/ as appropriate.
    • Record the total document count before batching.
  3. Batch-read docs — divide the corpus into batches of 5–10 files. For each batch:

    • Use read_file (for long docs) or grep_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.

Read the full file on GitHub · 120 lines

Changes

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.

  1. 2mo ago First seen · 120 lines · 78 tokens per session scan A 55451dc085df

Subscribe to this mod's changes

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.

Related

corpus-sweep compared with skills from other repositories

corpus-sweep next to 6 skills from other repositories
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