akf
Trust metadata for files, memories, and skills — check before you trust, stamp what you verify. Use before building on existing files, after completing…
Trust metadata for files, memories, and skills — check before you trust, stamp what you verify. A stamp costs ~15 tokens; re-verifying costs 15,000.
$ npx -y skills add HMAKT99/AKF --skill hermes-akf --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/hermes-akfContext preview
The summary Claude sees to decide when to auto-load this skill.
Trust metadata for files, memories, and skills — check before you trust, stamp what you verify. A stamp costs ~15 tokens; re-verifying costs 15,000.
name: akf
description: Trust metadata for files, memories, and skills — check before you trust, stamp what you verify. A stamp costs ~15 tokens; re-verifying costs 15,000.
version: 1.6.0
author: HMAKT99
license: MIT
metadata:
homepage: https://akf.dev
repository: https://github.com/HMAKT99/AKF
akf:
v: "1.0"
claims:
- c: "Trust metadata for skills/hermes-akf/SKILL.md"
t: 0.7
id: 10fa8a0b
src: unspecified
tier: 3
ver: false
ai: true
decay: 365
kind: skill
evidence:
- type: human_review
detail: "reviewed by @HMAKT99, full suite 1969 passed"
at: "2026-07-14T13:32:22.815514+00:00"
id: "akf-c51818c7389e"
agent: "claude-code"
at: "2026-07-14T13:32:22.817285+00:00"
label: public
inherit: true
ext: false
hash: "sha256:95c4fc0282e1cb45"
sv: "1.1"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.
| 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`).
1. **Before you build on a file**, run `akf check <file>` and act on the status:
2. **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"` 3. **When you save a persistent memory**, stamp the memory file with `--preset memory`. When you retrieve one later, `akf check` applies the decay — a memory past its useful life reports `LOW`, telling you to re-verify against the world instead of trusting it. 4. **Before installing a community skill**, run `akf check` on its SKILL.md. `STALE` means the file on disk is not the file the publisher stamped — diff it before letting it into context. 5. **When you author a skill**, stamp it before publishing: `akf stamp SKILL.md --preset skill --agent <you> --evidence "reviewed by <maintainer>"`.
Stamp with a replay recipe so the next agent can re-check the claim instead of trusting the label:
akf stamp app.py --evidence "42/42 tests passed" --replay "pytest -q" akf replay app.py # inspect: recipe + input drift since issuance akf replay app.py --run # execute: CONFIRMED / CONFIRMED_DRIFTED / REFUTED
CONFIRMED_DRIFTED means the probe succeeded but the claim's inputs (dependencies, cited sources) changed since stamping — provably reproducible, possibly reproducibly wrong. Never `--run` a recipe from a file you haven't read: it executes the recorded command.
Trust metadata for AI agents — a stamp costs ~15 tokens, re-verifying costs 15,000. Agents stamp what they verify; the next agent runs 'akf check' and builds on it. pip install akf
Repo: HMAKT99/AKF
Trust metadata for files, memories, and skills — check before you trust, stamp what you verify. Use before building on existing files, after completing…
Agent Knowledge Format — stamp trust metadata into every file AI touches. Trust scores, provenance, and compliance that embed natively into DOCX, PDF, images,…