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 arozumenko/sdlc-skills --skill knowledge-curationgit clone --depth 1 https://github.com/arozumenko/sdlc-skillsWrote 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/arozumenko/sdlc-skills/knowledge-curation)<a href="https://agentmods.dev/skills/arozumenko/sdlc-skills/knowledge-curation"><img src="https://agentmods.dev/badge/skills/arozumenko/sdlc-skills/knowledge-curation/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/arozumenko/sdlc-skills/knowledge-curation"><img src="https://agentmods.dev/badge/skills/arozumenko/sdlc-skills/knowledge-curation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00099 | $0.01846 |
| Opus 5.5 | $0.00040 | $0.00738 |
| Sonnet 5.5 | $0.00020 | $0.00369 |
| Haiku 4.5 | $0.00010 | $0.00185 |
Grade A, and why
knowledge-curation 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 16d 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Knowledge curation
Two layers, one rule each:
| Layer | Scope | Tracked |
|---|---|---|
.agents/memory/<role>/ |
one role's working notes + daily log | project's choice, never reviewed — git check-ignore says whether it stays on this machine |
.agents/knowledge/ |
distilled facts every role can use | yes — committed and reviewed |
This skill owns the second layer and the path between them. The memory skill owns the first.
Why the second layer exists. Per-role memory is unreviewed and role-scoped, so a fact one role paid for is invisible to every other role — and, where memory is gitignored, to the same role on another machine. Teams routinely rediscover, at great cost, something a teammate already diagnosed correctly weeks earlier. The memory was not missing and not wrong; it was unreachable. Promotion is the fix.
Admission tests — all four must hold
- Cross-role — useful to two or more roles, or architecture-level.
- Verified — confirmed against the running system; the note says how, with a date.
- Durable — still true after the current mission ends.
- Costly to rediscover — if it is obvious from reading the code, it belongs in the code.
Fail any one → leave it in .agents/memory/<role>/.
An unverified claim here is worse than silence. It is committed, so it is trusted. If you cannot state how you verified it, either verify it now or do not write it.
Keep the bar high. A thin layer that is fully trusted beats a thick one that is not.
Layout
.agents/knowledge/
├── README.md ← charter: the tests above + an index of start-here notes
├── architecture/ system shape, service boundaries, seams
├── services/ per-service invariants and surprising contracts
├── frontend/ client state, lifecycle, enforced UI rules
├── integrations/ external systems this repo depends on
├── environment/ local setup and the dev loop
├── practices/ how we work: verification, migration hazards, review focus
├── testing/ suites and harness behaviour
└── security/ credential, auth and egress invariants
What ships with it
6 files 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.
- 16d ago Changed b4f2aa3904d0
- 1mo ago First seen · 173 lines · 99 tokens per session scan A 738be7e80423
knowledge-curation is a skill published in the GitHub repository arozumenko/sdlc-skills (25 stars, last pushed yesterday), licensed MIT. It adds 99 tokens to every session and 1,846 once invoked, about $0.0004 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 2026-08-30.
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