Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/tonone-ai/tononenpx agentmods add skills/tonone-ai/tonone/apex-skillifyWrote 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/tonone-ai/tonone/apex-skillify)<a href="https://agentmods.dev/skills/tonone-ai/tonone/apex-skillify"><img src="https://agentmods.dev/badge/skills/tonone-ai/tonone/apex-skillify/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/tonone-ai/tonone/apex-skillify"><img src="https://agentmods.dev/badge/skills/tonone-ai/tonone/apex-skillify.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 | $0.00041 | $0.01055 |
| Opus 5.5 | $0.00016 | $0.00422 |
| Sonnet 5.5 | $0.00008 | $0.00211 |
| Haiku 4.5 | $0.00004 | $0.00105 |
Grade A, and why
apex-skillify 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 yesterday.
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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Apex Skillify
You are Apex — the engineering lead. Capture a flow that just succeeded as a permanent skill, so nobody re-derives it. Keep the skill short: description and body cost context on every load.
Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.
Steps
Step 0: Detect Where the Skill Lives
test -f scripts/sync-skills.py && test -d team && echo "tonone repo" || echo "user project"
Tonone repo: target is team/<agent>/skills/<name>/SKILL.md, then sync. User project: target is .claude/skills/<name>/SKILL.md.
Step 1: Confirm the Flow Is Worth Keeping
Check the session. Proceed only if all hold:
- The flow finished and its verification passed (tests green, command output correct, artifact produced).
- It is repeatable: a different input would run the same steps.
- It took more than a couple of commands, or had a non-obvious decision.
One-off fix, exploration, or unverified flow: refuse, say which test failed, and stop.
Step 2: Extract
From the session, list:
- Inputs: what the user supplied or the flow needed.
- Steps that worked: in order. Drop dead ends, retries, and abandoned approaches, but keep a one-line warning for any trap that cost real time.
- Decision points: where the path branched and what decided it.
- Verification: the exact command or check that proved success.
Step 3: Generalize
Replace hardcoded paths, names, versions, URLs, and project facts with a Step 0 detection (read config, glob, git remote, ask once via AskUserQuestion). Never bake secrets or one project's identifiers into the skill.
Step 4: Name and Own
- Name:
<agent>-<verb>, kebab-case. Pick the agent whose domain the flow belongs to (see docs/naming-guide.md). - Collision check:
ls team/*/skills/ skills/ 2>/dev/null | grep -x "<name>"and grepdocs/skill-index.jsonfor the name. On collision, extend or rename; never overwrite.
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.
- yesterday First seen · 90 lines · 41 tokens per session scan A 8c716910b05f
apex-skillify is a skill published in the GitHub repository tonone-ai/tonone (77 stars, last pushed yesterday), licensed MIT. It adds 41 tokens to every session and 1,055 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 2026-11-10.
apex-skillify compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| apex-skillifytonone-ai/tonone | Skill | 77 | yesterday | MIT | A | 41 | Claude Code |
| template-authoringCadasto/openehr-assistant-plugin | Skill | 6 | 1mo ago | MIT | A | 163 | Claude Code |
| archetype-lintCadasto/openehr-assistant-plugin | Skill | 6 | 1mo ago | MIT | A | 130 | Claude Code |
| sd-plan-testslukasrepublic/agentic-foundry | Skill | 0 | 5d ago | MIT | A | 133 | Claude Code |
| coding-conventionssandydasari/openacme | Skill | 90 | 3mo ago | MIT | A | 27 | Claude Code, Codex |
| bullmq-jobslukasrepublic/agentic-foundry | Skill | 0 | 5d ago | MIT | A | 0 | Claude Code |
| decommission-gatelukasrepublic/agentic-foundry | Skill | 0 | 5d ago | MIT | A | 185 | Claude Code |