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 agentmods add skills/lukasrepublic/agentic-foundry/research-capturenpx skills add lukasrepublic/agentic-foundry --skill research-capturegit clone --depth 1 https://github.com/lukasrepublic/agentic-foundryWrote 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/lukasrepublic/agentic-foundry/research-capture)<a href="https://agentmods.dev/skills/lukasrepublic/agentic-foundry/research-capture"><img src="https://agentmods.dev/badge/skills/lukasrepublic/agentic-foundry/research-capture.svg" alt="Measured on agentmods" 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 | $0.00147 | $0.01453 |
| Opus 5 | $0.00073 | $0.00727 |
| Sonnet 5 | $0.00029 | $0.00291 |
| Haiku 4.5 | $0.00015 | $0.00145 |
Grade A, and why
research-capture 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 2d 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/foundry:research-capture — durably persist the research gate's full evidence trail
The research-first record phase writes a distilled decision record (at the configured
governance.decisions_path, defaults to .foundry/decisions/) — the why. But the full claim-level evidence behind a deep-research run (every verified claim, its
adversarial vote, the source table, and crucially the refuted / killed claims) lives only in an
ephemeral workflow-output file and is lost on cleanup. So a later auditor asking "was this 'industry
consensus' actually real?" has only the author's summary. This discipline closes that gap the standard
way — a durable template + an author convention, exactly as the ADR / decision-record ecosystem
does (adr-tools / log4brains / MADR ship new/link scaffolders + templates; none ship a
byte-identical emitter or a fail-closed completeness classifier).
It is a DISCIPLINE, not a code helper (the deep-spec-audit re-ground)
The v1 design — a deterministic byte-identical capture helper + a fail-closed completeness validator —
was novel machinery for a solved problem (a deep-spec-audit category-error). Determinism / byte-identity has no
prior-art basis for a human-read prose doc (it governs machine-consumed attestations, not narratives).
The hand-written .foundry/research/wf_c3c6df43-3b5-machinery-view.md — complete, with a Refuted/Killed
section + both-way ADR links, authored with zero new code — is the decisive disproof. So capture is
authoring from a template; the lightweight drop-in wiring lint this line originally shipped
was removed with the drop-in-check registry and was not ported (see the note below) — capture
ships no code.
The discipline
At a deep-research-bearing research-first gate (a multi-source run, not a mechanical/obvious-standard decision):
- Persist the full trail. Author
<run-id>-<slug>.mdat the configured governance-record research location —governance.research_pathin.claude/foundry-project.json(defaults to.foundry/research/) — fromresearch-artifact-template.md(this skill's sibling). The<run-id>-<slug>filename is path-safe ([a-z0-9._-]). Required sections: the run-id, the question, the stats (sources / claims / verified / confirmed / refuted), the verified claims, the## Refuted / disconfirming evidencesection (REQUIRED — present even if(none)), the sources table, and a both-way link with the decision record. - Retain the disconfirming evidence in the ADR too. Author the ADR — at the configured
governance-record decisions location (
governance.decisions_pathin.claude/foundry-project.json, defaults to.foundry/decisions/) — with a## Refuted / disconfirming evidencesection (Nygard Consequences-style) so the killed/disconfirming claims are retained in the decision record itself as well as the linked artifact. - Link both ways. The ADR points at the artifact; the artifact points at the ADR.
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.
- 2d ago First seen · 77 lines · 147 tokens per session scan A 33abe5602dfb
research-capture is a skill published in the GitHub repository lukasrepublic/agentic-foundry (1 stars, last pushed today), licensed MIT. It adds 147 tokens to every session and 1,453 once invoked, about $0.0007 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 2026-09-03.
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