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 All-The-Vibes/ATV-Phoenix --skill phoenix-okfgit clone --depth 1 https://github.com/All-The-Vibes/ATV-PhoenixWrote 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/all-the-vibes/atv-phoenix/phoenix-okf)<a href="https://agentmods.dev/skills/all-the-vibes/atv-phoenix/phoenix-okf"><img src="https://agentmods.dev/badge/skills/all-the-vibes/atv-phoenix/phoenix-okf/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/all-the-vibes/atv-phoenix/phoenix-okf"><img src="https://agentmods.dev/badge/skills/all-the-vibes/atv-phoenix/phoenix-okf.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 | $0.00108 | $0.01085 |
| Opus 5.5 | $0.00043 | $0.00434 |
| Sonnet 5.5 | $0.00022 | $0.00217 |
| Haiku 4.5 | $0.00011 | $0.00109 |
Grade A, and why
phoenix-okf 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 1mo 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
phoenix-okf — knowledge that pays rent in the open
Overview
OKF (Open Knowledge Format) is a vendor-neutral spec for
representing knowledge as a directory of markdown files with YAML frontmatter — one required key
(type), graph-shaped via plain markdown links, with index.md for progressive disclosure. It
is the format Phoenix's Context Assembly pillar already implies: pay once to understand
structure, then never again. This skill makes that knowledge portable and inspectable
instead of trapped in an opaque .token-master/graph.json.
A bundle is a directory. If you can
cata file you can read it; if you cangit cloneit you can ship it.
When to use
- You have a graphed repo (
.token-master/graph.json) and want the knowledge human-readable, diffable, and consumable by any tool (Obsidian, the OKF graph viewer, another agent). - You want skill discovery to ride a standard progressive-disclosure format.
- You want to feed an external OKF bundle (a data catalog, runbooks, org knowledge) into a Phoenix run as cheap context.
When NOT to use: a single local lookup grep answers in one turn. OKF earns its place on reusable, shareable knowledge, not one-off questions.
Three moves
1. Produce — code graph → OKF bundle
python scripts/okf_export.py --graph .token-master/graph.json --out okf-out --name <repo>
One concept document per source file; cross-file edges become bundle-relative markdown links.
INFERRED (name-matched, ~0.8-confidence) edges are flagged candidate — verify at the cited
file:line before trusting one for a risky change (phoenix-context honesty rule). Auto-writes
per-directory index.md, a root index.md (declaring okf_version), and a log.md.
2. Validate — the objective gate
python scripts/okf_validate.py okf-out
Checks OKF §9 conformance: every non-reserved .md has parseable frontmatter and a non-empty
type; reserved files (index.md/log.md) follow their rules. Exit 0 = conformant — use it as
a phoenix_sense check. Broken cross-links are tolerated per spec (warning, not error) unless
--strict-links.
What ships with it
10 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.
- checks/okf-conformant.json 126 B
- checks/okf-fresh.json 164 B
- checks/README.md 1.2 KB
- references/OKF-SPEC-0.1.md 15 KB
- scripts/okf_common.py 4.0 KB runs code
- scripts/okf_export.py 11 KB runs code
- scripts/okf_freshness.py 2.6 KB runs code
- scripts/okf_ingest.py 5.4 KB runs code
- scripts/okf_skillsync.py 3.6 KB runs code
- scripts/okf_validate.py 5.7 KB runs code
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.
- 1mo ago First seen · 80 lines · 108 tokens per session scan A 7b8b3faed256
phoenix-okf is a skill published in the GitHub repository All-The-Vibes/ATV-Phoenix (6 stars, last pushed 6d ago), licensed MIT. It adds 108 tokens to every session and 1,085 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 2026-08-31.
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