Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add 42-evey/claude-research-pipeline --skill research-consumegit clone --depth 1 https://github.com/42-evey/claude-research-pipelineWrote 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/42-evey/claude-research-pipeline/research-consume)<a href="https://agentmods.dev/skills/42-evey/claude-research-pipeline/research-consume"><img src="https://agentmods.dev/badge/skills/42-evey/claude-research-pipeline/research-consume/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/42-evey/claude-research-pipeline/research-consume"><img src="https://agentmods.dev/badge/skills/42-evey/claude-research-pipeline/research-consume.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 | $0.00028 | $0.01821 |
| Opus 5 | $0.00014 | $0.00911 |
| Sonnet 5 | $0.00006 | $0.00364 |
| Haiku 4.5 | $0.00003 | $0.00182 |
Grade A, and why
research-consume 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 11d 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 — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Consume — Process Raw Docs Into Meta-Knowledge
Based on the Karpathy autoresearch pattern (verified: Fortune, VentureBeat, 26K GitHub stars):
- Editable asset: The meta-doc is the asset that improves with each cycle
- Scalar metric: Claims verified count, depth/accuracy scores, compression ratio (raw bytes consumed vs meta-doc growth)
- Time box: Max 3 docs per cycle, ~100K tokens budget, 8 min per doc
Each cycle: read what you know (meta-doc) → consume what's new (raw docs) → verify claims → improve the asset → archive consumed inputs. The meta-docs compound over time — each cycle makes them more verified, more compressed, more useful.
Check if config exists at ${CLAUDE_PLUGIN_DATA}/config.json. If not, or if research_dirs is empty:
- Ask the user: "Which directories contain research documents to process?"
- Default to current working directory if they don't specify
- Set
meta_dirto./research/meta(relative to cwd) - Set
archive_dirto./research/archive - Set
reviews_dirto./research/reviews - Create all dirs that don't exist
- Save config to
${CLAUDE_PLUGIN_DATA}/config.json
All paths should be relative to the current working directory unless the user specifies absolute paths.
Step 1: Index & Categorize
List all raw .md docs across configured research directories. Group them by category (ai-models, infrastructure, revenue, agent, iot-protocols, social-media, etc.).
Step 2: Pick ONE Category
Choose the category with the most unprocessed raw docs. You will process up to 3 docs from this SAME category. All docs in a batch go into the SAME meta-doc.
Step 3: Read Existing Meta-Doc FIRST
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 182 lines · 28 tokens per session scan A 22e3469bf966
research-consume is a skill published in the GitHub repository 42-evey/claude-research-pipeline (6 stars, last pushed 1mo ago), licensed MIT. It adds 28 tokens to every session and 1,821 once invoked, about $0.0001 per session on Opus 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.
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