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 agentmods add skills/rhtevan/agentfs/agentfs-evalnpx skills add rhtevan/agentfs --skill agentfs-evalgit clone --depth 1 https://github.com/rhtevan/agentfsWhat 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 | $0.00016 | $0.02894 |
| Opus 5 | $0.00008 | $0.01447 |
| Sonnet 5 | $0.00003 | $0.00579 |
| Haiku 4.5 | $0.00002 | $0.00289 |
Grade A, and why
agentfs-eval 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 2d 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 — 271 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AgentFS Eval
Assess the health and maturity of an AgentFS workspace through three layers of progressively deeper verification.
Overview
| Property | Value |
|---|---|
| Version | 1.0 |
| Trigger | Explicit only — user asks to run eval |
| Scope | Evaluates a PROJECT or LITE-scoped .agents/ directory |
| LITE scope | Skips skills/profiles L1 checks; adds LITE exclusion assertions |
| Dependencies | bash, find, grep, stat, git (optional but recommended) |
| LLM required | Layer 3 only (semantic rubrics) |
Recommended Usage
For the most reliable evaluation, run this skill in a fresh session against the target project directory. This eliminates conversational bias from prior work in the same session.
Example prompts:
"Run agentfs eval" "Run agentfs eval against /home/user/projects/my-project"
The skill works against any directory containing .agents/ — it does
NOT need to be the current working directory. If no path is provided,
it defaults to the current working directory.
Why a Fresh Session?
- Eliminates self-evaluation bias — the agent that did the work should not be the one evaluating it
- Removes conversational context — no memory of what the user "wanted," just cold assessment of filesystem state
- Reduces sycophancy pressure — no incentive to report good results to please the user who just watched it work
- More capable models give stronger classification accuracy for Layer 3 semantic rubrics
Maturity Levels
| Level | Name | Requirements |
|---|---|---|
| L0 | Absent | No .agents/ directory exists |
| L1 | Scaffolded | .agents/ exists with valid structure |
| L2 | Structurally Sound | All Layer 1 assertions pass |
| L3 | Behaviorally Safe | Layer 1 + Layer 2 assertions pass |
| L4 | Semantically Accurate | Layer 1 + Layer 2 + Layer 3 assertions pass |
| L5 | Self-Correcting | Agent can run eval, detect violations, and fix them |
What ships with it
9 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.
- CHANGELOG.md 360 B
- references/design-decisions.md 9.1 KB
- rubrics/memory-classification.yaml 1.4 KB
- rubrics/reference-verification.yaml 1.8 KB
- rubrics/skill-accuracy.yaml 2.5 KB
- rubrics/sycophancy-detection.yaml 1.9 KB
- scripts/agentfs-behavior.sh 11 KB runs code
- scripts/agentfs-check.sh 13 KB runs code
- templates/report.md 1.4 KB
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.
- 2d ago First seen · 271 lines · 16 tokens per session scan A 3c150d865b76
agentfs-eval is a skill published in the GitHub repository rhtevan/agentfs (2 stars, last pushed 3d ago), licensed Apache-2.0. It adds 16 tokens to every session and 2,894 once invoked, about $0.0001 per session on Opus 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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