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/winstonkoh87/Athena-Publicnpx agentmods add skills/winstonkoh87/athena-public/skill-compilerWrote 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/winstonkoh87/athena-public/skill-compiler)<a href="https://agentmods.dev/skills/winstonkoh87/athena-public/skill-compiler"><img src="https://agentmods.dev/badge/skills/winstonkoh87/athena-public/skill-compiler/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/winstonkoh87/athena-public/skill-compiler"><img src="https://agentmods.dev/badge/skills/winstonkoh87/athena-public/skill-compiler.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 | $0.00046 | $0.01709 |
| Opus 5.5 | $0.00018 | $0.00684 |
| Sonnet 5.5 | $0.00009 | $0.00342 |
| Haiku 4.5 | $0.00005 | $0.00171 |
Grade A, and why
skill-compiler 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 2mo 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 — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Compiler — Solved-to-Skill Automation
Source: Hermes Agent by Nous Research (May 2026) Core Claim: "It's the only agent with a built-in learning loop — it creates skills from experience." Athena Adaptation: Hermes does this via Python (
agent/curator.py+tools/skill_usage.py). Athena does it via workflow-level pattern detection + markdown SKILL.md generation.
The Problem This Solves
Athena currently relies on manual insight filing during /end sessions. The [S] and [V] markers in session logs capture learnings, but they remain trapped in session logs — they don't become reusable skills automatically.
Hermes solved this: when the agent completes a novel task, it automatically creates a new skill from the solution, so the same problem class never requires re-derivation.
When to Use
Automatic Trigger (Post-Task Detection)
After any task completion where ALL of the following are true:
- Novelty: The task required a solution path not covered by any existing skill
- Complexity: Task took ≥5 agent turns OR involved ≥3 tool calls
- Success: User confirmed the solution worked (explicit or implicit — no corrections in final 2 turns)
- Reusability: The solution generalizes beyond this specific instance
Manual Trigger
User says: "compile this into a skill", "save this as a skill", "I want to remember how we did this"
Execution Flow
Phase 1: Pattern Extraction (Analysis)
Perform private analysis in <analysis> tags (not written to files):
<analysis>
1. What was the PROBLEM CLASS? (Not the specific instance)
- e.g., "Pairs trading dashboard with cointegration analysis"
- NOT "Dashboard 4-decimal rounding fix"
2. What was the SOLUTION ARCHITECTURE?
- Key steps in order
- Tools/APIs used
- Decision points and their resolution criteria
3. What were the FAILURE MODES encountered?
- What went wrong initially?
- What heuristics resolved it?
4. What is the REUSE SURFACE?
- When would someone encounter this problem class again?
- What context_trigger keywords would match?
5. OVERLAP CHECK
- Which existing skills partially cover this?
- Is this better as a new skill or a subsection of an existing one?
</analysis>
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.
- 2mo ago First seen · 179 lines · 46 tokens per session scan A 8bb2e5fef362
skill-compiler is a skill published in the GitHub repository winstonkoh87/Athena-Public (620 stars, last pushed today), licensed MIT. It adds 46 tokens to every session and 1,709 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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