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/extract-specnpx skills add lukasrepublic/agentic-foundry --skill extract-specgit 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/extract-spec)<a href="https://agentmods.dev/skills/lukasrepublic/agentic-foundry/extract-spec"><img src="https://agentmods.dev/badge/skills/lukasrepublic/agentic-foundry/extract-spec.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 | $0.00113 | $0.01363 |
| Opus 5 | $0.00056 | $0.00681 |
| Sonnet 5 | $0.00023 | $0.00273 |
| Haiku 4.5 | $0.00011 | $0.00136 |
Grade A, and why
extract-spec 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 4d 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 — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/foundry:extract-spec
Turn existing code into functional specifications. You survey a codebase, mine the behavior it actually
enforces, and produce a candidate atomic spec — which then flows through the normal front door
(/foundry:intake → /foundry:spec-review → /foundry:authorize). You are read-heavy and write only a candidate
draft; you never authorize, merge, or baseline.
The load-bearing discipline (read first)
- Extracted ≠ authorized, and extracted ≠ desired. The code may encode bugs; a snapshot of current behavior
is a characterization, not a specification of intent. Therefore the output is an un-authorized candidate
draft that MUST be routed through
/foundry:intake(→/foundry:spec-review→/foundry:authorize). Never emit an authorized or "baseline truth" spec, and never freeze a contract from extraction. The front-authorization floor is preserved: extracted behavior becomes normative only after the operator authorizes it. - Never invent behavior. If the code does not clearly express a contract, record it as a
[NEEDS CLARIFICATION: <question>]marker — do not fabricate a requirement (Example Mapping's Question card). - Cross-validate against callers. The real contract is what callers rely on, not what a docstring claims (characterization-test discipline — capture ACTUAL, not intended, behavior; note it can pin existing bugs, so surface anything surprising as an uncertainty rather than "correcting" it).
Prior art / industry grounding
Grounded in prior-art research on the code-to-spec mechanism (how brownfield code is safely mined into a candidate spec) and on the emit shape (the template a mined capability is promoted into). Sources: Feathers, Working Effectively with Legacy Code (characterization testing); Adzic Specification by Example + Wynne's Example Mapping (flag uncertainty, don't invent); EARS/ISO-29148 (the Requirement/Invariant, measurable shape). Comparable prior art in other spec-driven tooling (e.g. spec-mining features) is one corroborating datapoint, not the source.
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.
- 4d ago First seen · 88 lines · 113 tokens per session scan A 9cb4f4f9c4de
extract-spec is a skill published in the GitHub repository lukasrepublic/agentic-foundry (1 stars, last pushed 2d ago), licensed MIT. It adds 113 tokens to every session and 1,363 once invoked, about $0.0006 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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