Borrowing it
Nothing to install: this file belongs to generative-computing/mellea-skills-compiler. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/generative-computing/mellea-skills-compiler/main/.claude/commands/mellea-fy-map.mdgit 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/commands/generative-computing/mellea-skills-compiler/mellea-fy-map)<a href="https://agentmods.dev/commands/generative-computing/mellea-skills-compiler/mellea-fy-map"><img src="https://agentmods.dev/badge/commands/generative-computing/mellea-skills-compiler/mellea-fy-map.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.02285 |
| Opus 5 | $0.00000 | $0.01143 |
| Sonnet 5 | $0.00000 | $0.00457 |
| Haiku 4.5 | $0.00000 | $0.00229 |
Grade A, and why
mellea-fy-map 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 8d 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 — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Melleafy Step 2: Element-to-Primitive Mapping
Version: 4.1.0 | Prereq: inventory.json, classification.json | Produces: element_mapping.json
Schema: Output
intermediate/element_mapping.jsonMUST conform to.claude/schemas/element_mapping.schema.json.
Step 2 reads inventory.json and produces element_mapping.json — the routing decision for every element: which file in the generated package, which symbol, which Mellea primitive.
Important: Step 2 does NOT commit dispositions for tool-dependent elements. Every TOOL_TEMPLATE mapping entry is provisional (final_target_file: "pending_step_2.5"). Step 2.5 decides real_impl vs stub vs mock and amends.
Tag-to-primitive table
| Tag | Primary primitive | Target file | Notes |
|---|---|---|---|
EXTRACT |
@generative slot |
slots.py |
Two-step pattern when schema complexity warrants (§below) |
CLASSIFY |
@generative slot |
slots.py |
Return type: -> Literal[...] — Ollama supports constrained decoding |
GENERATE |
m.instruct(format=Schema) |
inline in pipeline.py |
format= always a concrete Pydantic model, never dict |
VALIDATE_OUTPUT |
Requirement |
requirements.py |
Uses validation_fn=simple_validate(...) for structural checks; bare description for semantic checks |
VALIDATE_DOMAIN |
m.instruct(format=DomainSchema) |
inline in pipeline.py |
Checks external artifacts; produces structured verdict, not pass/fail boolean |
TRANSFORM |
m.transform() or m.instruct(format=Schema) |
inline in pipeline.py |
m.transform() when types are known; m.instruct when transformation needs prompted reasoning |
QUERY |
m.query() |
inline in pipeline.py |
Read-only question against data already in scope |
DECIDE |
m.instruct(format=DecisionSchema) |
inline in pipeline.py |
Gates remediation loops (see Remediate below) |
ORCHESTRATE |
Plain Python control flow | pipeline.py |
Not a Mellea primitive — describes flow (sequential phases, branches, loops) |
CONVERSE |
m.chat(), pipeline parameter, or NotImplementedError stub |
varies | Three realisations — see below |
REMEDIATE |
Bounded while loop with m.instruct(format=PatchSchema) |
pipeline.py |
Three mapping entries: modification + evaluation + loop wrapper |
SCHEMA |
Pydantic BaseModel class |
schemas.py |
One class per schema; no nested submodels buried in function defs |
CONFIG |
Final[T] constant |
config.py |
Under # === C<N> ... === section header |
TOOL_TEMPLATE |
Python function | tools.py (provisional) |
Amended by Step 2.5d based on disposition |
DETERMINISTIC |
Plain Python function | pipeline.py or tools.py |
tools.py when shared across branches or >15 lines |
TOOL_INPUT |
Pipeline parameter or loader.py call |
main.py or loader.py |
Data a tool produces that feeds the pipeline |
NO_DECOMPOSE |
No primitive | — | Recorded in element_mapping.json with primitive: "none" for invariant completeness |
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.
- 8d ago First seen · 157 lines · 0 tokens per session scan A a929dc8fcd60
mellea-fy-map is a command published in the GitHub repository generative-computing/mellea-skills-compiler (48 stars, last pushed today), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 2,285 tokens. 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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