Borrowing it
Nothing to install: this file belongs to dbcls/togomcp. 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/dbcls/togomcp/main/.claude/skills/mie-generator/SKILL.mdgit clone --depth 1 https://github.com/dbcls/togomcpWrote 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/dbcls/togomcp/mie-generator)<a href="https://agentmods.dev/skills/dbcls/togomcp/mie-generator"><img src="https://agentmods.dev/badge/skills/dbcls/togomcp/mie-generator.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 | $0.00208 | $0.17969 |
| Opus 5 | $0.00104 | $0.08984 |
| Sonnet 5 | $0.00042 | $0.03594 |
| Haiku 4.5 | $0.00021 | $0.01797 |
Grade A, and why
mie-generator 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 7d 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 — 625 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MIE File Generator
An MIE file is a compact YAML document that describes an RDF database well enough for an LLM to write correct, efficient SPARQL against it on the first try. Good MIE files are the difference between "Claude writes a working query" and "Claude times out the endpoint with a FILTER(CONTAINS()) over 244M triples".
Format: v3. The authorable contract is togo_mcp/data/docs/MIE_v3_spec.md — read it before writing. v3 is organized by agent need × recoverability with the verified, executable worked example as the atomic unit: five need-based parts (database, discovery, the header, examples, schema_delta, id_join_map), where each example simultaneously is the schema shape, the sample triple, and (via traps_avoided) the warning it would otherwise be written as three or four times. The worked reference is the hand-authored pilot togo_mcp/data/mie/uniprot.yaml. Carry only what the model cannot recover on its own (spec §4.3); where this skill and the spec disagree, the spec wins.
This skill lives in a Claude Code environment with filesystem access and SPARQL execution tools (from the togomcp_local MCP server). Use filesystem tools freely — that is the normal mode of operation here.
The Two Hard Rules
1. No blind SPARQL retry loops. Schema discovery legitimately requires many queries, but if a query fails twice in a row, stop and diagnose — wrong predicate, wrong graph, wrong IRI pattern — before retrying. More retries without diagnosis do not fix a structurally wrong query.
2. Nothing in the MIE file is invented — and "it ran" is not "it's right." Every examples entry must be executed against the real endpoint before the file is written, its live result recorded in the verified: block with a date:, and that result confirmed correct, not merely error-free:
- SPARQL (every
examples[].sparql, including theaggregationandcross_dbones): must run AND return the right thing. A query that succeeds but returns a union-inflated COUNT is a failed test, not a passing one — scope the graph and verify the figure (Phase 2g / 5c). Theverified:block records the actual figure you saw, so a later re-run that disagrees is a drift signal, not silent rot. - Search-wrapper claims: any assertion the file makes about a
search_*/ncbi_esearch/OLS4:searchClassestool's behavior (e.g. "usesearch_chembl_targetfor targets, EGFR → CHEMBL203") must be run through the actual tool and the claimed hit confirmed to appear at a usable rank/limit — not buried at rank 5 behind unrelated hits, and present at the limit the claim implies (Phase 5e).
What ships with it
5 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.
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.
- 7d ago First seen · 625 lines · 208 tokens per session scan A 7b84f0a5e4d5
mie-generator is a skill published in the GitHub repository dbcls/togomcp (13 stars, last pushed 4d ago), licensed MIT. It adds 208 tokens to every session and 17,969 once invoked, about $0.0010 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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