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 generative-computing/mellea-skills-compiler --skill mellea-fy-fixturesgit clone --depth 1 https://github.com/generative-computing/mellea-skills-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/generative-computing/mellea-skills-compiler/mellea-fy-fixtures)<a href="https://agentmods.dev/skills/generative-computing/mellea-skills-compiler/mellea-fy-fixtures"><img src="https://agentmods.dev/badge/skills/generative-computing/mellea-skills-compiler/mellea-fy-fixtures/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/generative-computing/mellea-skills-compiler/mellea-fy-fixtures"><img src="https://agentmods.dev/badge/skills/generative-computing/mellea-skills-compiler/mellea-fy-fixtures.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 | $0.00018 | $0.01285 |
| Opus 5 | $0.00009 | $0.00642 |
| Sonnet 5 | $0.00004 | $0.00257 |
| Haiku 4.5 | $0.00002 | $0.00128 |
Grade A, and why
mellea-fy-fixtures 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 11d 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Melleafy Step 4: Fixture Generation
Version: 4.2.1 | Prereq: Step 3 complete (skeleton emitted with finalised run_pipeline signature) | Produces: fixtures_emission.json
Schema: Output
intermediate/fixtures_emission.jsonMUST conform toschemas/fixtures_emission.schema.json
Output path rule (Rule OUT-4): Step 4 produces ONLY
intermediate/fixtures_emission.jsonin the intermediate directory. This JSON file contains fixture specifications that will be used by downstream processes. DO NOT generate any Python source files — nofixtures/directory, no.pyfiles, no__init__.py. The fixture source code generation is handled by a separate process outside this skill.
CRITICAL: This step generates ONLY the JSON specification file.
Step 4 generates fixture specifications for 5–8 test fixtures covering ≥3 C-categories. The output is a single JSON file conforming to the schema.
Rule 4-1 — JSON-only fixture specification: Generate all fixture specifications in a single JSON object conforming to
schemas/fixtures_emission.schema.json. The invocation receives therun_pipelinesignature, the element mapping summary, and the C-category coverage requirement, and returns one JSON object — not Python source. This skill's output is ONLY the JSON file. Do not generate Python fixture files, do not create afixtures/directory, do not write__init__.pyor individual fixture modules.
CRITICAL: Input parameter matching
The keys in every fixture's inputs object MUST be identical to the parameter names of the run_pipeline function in pipeline.py. This is not optional. A fixture with {"text": "..."} for a pipeline that expects run_pipeline(user_query=...) will fail at runtime with a TypeError. Before emitting JSON, verify the exact parameter names from the generated pipeline function. The schema cannot enforce this — it's the model's responsibility to match.
Fixture structure
The model emits one JSON object saved as intermediate/fixtures_emission.json. This is the only output of Step 4.
What ships with it
1 file 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.
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.
- 11d ago First seen · 106 lines · 18 tokens per session scan A fb3f1f071a55
mellea-fy-fixtures is a skill published in the GitHub repository generative-computing/mellea-skills-compiler (49 stars, last pushed today), licensed Apache-2.0. It adds 18 tokens to every session and 1,285 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 2026-08-30.
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