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 HMAKT99/AKF --skill hermes-akfgit clone --depth 1 https://github.com/HMAKT99/AKFWrote 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/hmakt99/akf/hermes-akf)<a href="https://agentmods.dev/skills/hmakt99/akf/hermes-akf"><img src="https://agentmods.dev/badge/skills/hmakt99/akf/hermes-akf/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/hmakt99/akf/hermes-akf"><img src="https://agentmods.dev/badge/skills/hmakt99/akf/hermes-akf.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 | $0.00044 | $0.01395 |
| Opus 5.5 | $0.00018 | $0.00558 |
| Sonnet 5.5 | $0.00009 | $0.00279 |
| Haiku 4.5 | $0.00004 | $0.00139 |
Grade A, and why
akf 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 8d 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AKF — Agent Knowledge Format
Leave trust metadata on everything you produce, and check it on everything you consume. Stamps are notes agents leave for the next agent (including future you): what was done, what was verified, how much to trust it now.
When to Use
- Before building on any existing file — check whether its verification is still valid instead of re-verifying from scratch
- After creating or modifying a file — stamp it with the evidence you actually observed
- Before loading a community skill someone else published — verify it hasn't been modified since the publisher stamped it
- When saving or retrieving persistent memories — stale memories should decay, not be trusted forever
Quick Reference
| Command | What it does |
|---|---|
akf check <file> |
One line: OK / LOW / STALE / UNSTAMPED + trust, evidence, age. Exit 0/1/2. |
akf stamp <file> --agent <you> --evidence "<observed>" |
Stamp with evidence (auto-classified: test_pass, human_review, ci_pass…) |
akf stamp <file> --preset memory |
Memory stamp: trust decays with a 30-day half-life |
akf stamp <file> --preset skill |
Skill stamp: public, supply-chain provenance |
akf init |
Wire git + agent hooks so stamping is automatic |
akf scan <dir> --recursive |
Trust report for a whole directory |
Install once: pip install akf (or pipx install akf).
Procedure
- Before you build on a file, run
akf check <file>and act on the status:OK(exit 0) — fresh stamp with verified evidence. Build on it; skip re-verification.LOW(exit 1) — stamped but unverified, or trust has decayed. Verify before trusting.STALE(exit 1) — the file changed after it was stamped. Re-verify before trusting.UNSTAMPED(exit 2) — no provenance. Treat as unverified.
- After you create or modify a file, stamp it with the strongest evidence you actually observed:
akf stamp report.py --agent hermes --evidence "42/42 tests passed" - When you save a persistent memory, stamp the memory file with
--preset memory. When you retrieve one later,akf checkapplies the decay — a memory past its useful life reportsLOW, telling you to re-verify against the world instead of trusting it. - Before installing a community skill, run
akf checkon its SKILL.md.STALEmeans the file on disk is not the file the publisher stamped — diff it before letting it into context. - When you author a skill, stamp it before publishing:
akf stamp SKILL.md --preset skill --agent <you> --evidence "reviewed by <maintainer>".
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.
- 8d ago Changed 21f56873fc7b
- 9d ago Changed · +3 lines · +5 tokens per session 00925d5e8ba2
- 2mo ago First seen · 97 lines · 39 tokens per session scan A 600786a3720e
akf is a skill published in the GitHub repository HMAKT99/AKF (20 stars, last pushed 5d ago), licensed MIT. It adds 44 tokens to every session and 1,395 once invoked, about $0.0002 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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