Borrowing it
Nothing to install: this file belongs to morluto/jacobian. 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/morluto/jacobian/main/.agents/skills/evaluate-mcp-tool-adoption/SKILL.mdgit clone --depth 1 https://github.com/morluto/jacobianWrote 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/morluto/jacobian/evaluate-mcp-tool-adoption)<a href="https://agentmods.dev/skills/morluto/jacobian/evaluate-mcp-tool-adoption"><img src="https://agentmods.dev/badge/skills/morluto/jacobian/evaluate-mcp-tool-adoption/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/morluto/jacobian/evaluate-mcp-tool-adoption"><img src="https://agentmods.dev/badge/skills/morluto/jacobian/evaluate-mcp-tool-adoption.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 | $0.00023 | $0.00787 |
| Opus 5 | $0.00012 | $0.00394 |
| Sonnet 5 | $0.00005 | $0.00157 |
| Haiku 4.5 | $0.00002 | $0.00079 |
Grade A, and why
evaluate-mcp-tool-adoption 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 5d 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Evaluate MCP Tool Adoption
Evaluate an agent-facing tool as a routing surface, not as a call-count target. Distinguish availability, discovery, selection, and execution before changing server instructions, tool metadata, or the operation contract. Load this skill only for the evaluator; never enable it in an agent-under-test configuration.
Use harbor-benchmarks for a Harbor task or verifier change and
verifier-evaluations for its mathematical verifier. This skill owns only the
adoption diagnosis and its evidence boundary.
Freeze the question
For a controlled comparison, write one falsifiable question, such as “does server-level guidance cause an agent to inspect a matching operation when the ordinary prompt does not?” Keep the model, model version, reasoning effort, client version, Jacobian revision, image digest, task digest, MCP configuration, egress/proxy state, attempt count, and budgets fixed across comparable arms.
Record the relevant prompt and agent-visible MCP surface. In a controlled comparison, do not include an operation ID, answer, or routing instruction in a natural-use arm. Do not score a tool call as success: final mathematical correctness, declared witness validity, and truthful claims remain the task outcomes.
Establish the four-stage control matrix
Run deterministic checks before model calls, then use the smallest set of model arms that distinguishes the suspected stage.
| Stage | Minimal probe | What a pass establishes |
|---|---|---|
| Availability | Start the configured MCP server and inspect the initialization/tool list. | The client receives the intended connection, tools, descriptions, and schemas. |
| Discovery | Search with a natural user phrase and natural category; inspect only returned candidates. | A relevant operation is reachable without prior taxonomy or exact-ID knowledge. |
| Execution | Invoke the known matching operation directly with one frozen valid payload. | Input schema, dispatch, and typed result work. |
| Selection | Give a fresh agent the same mathematical task under no cue, server guidance only, and one clearly labeled task-level routing cue. | The effect of routing/salience is separable from connection and execution. |
What ships with it
2 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.
- 5d ago Changed · -30 lines · -57 tokens per session 9721f8255ff5
- 10d ago First seen · 107 lines · 80 tokens per session scan A c7c93c777eac
evaluate-mcp-tool-adoption is a skill published in the GitHub repository morluto/jacobian (190 stars, last pushed today), licensed MIT. It adds 23 tokens to every session and 787 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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