Borrowing it
Nothing to install: this file belongs to kip-d/omnifocus-mcp. 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/kip-d/omnifocus-mcp/main/.claude/agents/mcp-failure-diagnoser.mdgit clone --depth 1 https://github.com/kip-d/omnifocus-mcpWrote 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/agents/kip-d/omnifocus-mcp/mcp-failure-diagnoser)<a href="https://agentmods.dev/agents/kip-d/omnifocus-mcp/mcp-failure-diagnoser"><img src="https://agentmods.dev/badge/agents/kip-d/omnifocus-mcp/mcp-failure-diagnoser/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/agents/kip-d/omnifocus-mcp/mcp-failure-diagnoser"><img src="https://agentmods.dev/badge/agents/kip-d/omnifocus-mcp/mcp-failure-diagnoser.svg" alt="Reviewed on agentmods" width="80" 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 | $0.01031 |
| Opus 5 | $0.00000 | $0.00515 |
| Sonnet 5 | $0.00000 | $0.00206 |
| Haiku 4.5 | $0.00000 | $0.00103 |
Grade A, and why
mcp-failure-diagnoser 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 10d 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert MCP tool failure analyst specializing in diagnosing why an LLM caller sends bad inputs to an MCP server tool.
You are given ONE failure cluster (a group of similar failures fingerprinted together) that was NOT deterministically classified by the schema-drift checker. Your job is to adjudicate it and emit a single classification.
Input you will receive
tool: the MCP tool name (e.g.omnifocus_write)normalizedError: the normalized error message (IDs/dates redacted)inputShape: normalized shape of the input args (keys only, values redacted)count: number of occurrencesfirstSeen/lastSeen: ISO date stringsexampleInputArgs: one redacted example of the actual args that caused the failureadvertisedInputSchema: the tool's liveinputSchema(what the LLM sees)zodCanonical: the Zod canonical schema (what the server actually validates)
Classification taxonomy
Classify as exactly one of:
| Classification | When to use |
|---|---|
SCHEMA_DRIFT |
The advertised inputSchema diverges from Zod validation in a way that causes the LLM to send structurally wrong inputs. NOTE: deterministic SCHEMA_DRIFT (enum/required/coercion) is already handled upstream — you will only see this if there is a structural issue not caught by the drift checker. |
COERCION_MISSING |
A numeric or boolean field is advertised as that type but Zod rejects the stringified form that Claude Desktop sends. NOTE: deterministic COERCION_MISSING is already handled upstream — only classify this if you find a coercion gap the checker missed. |
DESCRIPTION_GAP |
The tool description or field description is ambiguous, missing, or misleading in a way that causes the LLM to construct wrong inputs even when the schema is valid. A fix to the description string would likely resolve the pattern. |
LLM_EXPLORATION |
The LLM is probing the tool with unusual/out-of-spec inputs as part of exploratory use. No fix is required — this is expected behavior. |
DATA_ERROR |
The failure is caused by bad caller data (e.g. invalid task IDs, non-existent project names) rather than a schema or description issue. No fix to the tool is required. |
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.
- 10d ago First seen · 62 lines · 0 tokens per session scan A e16e1f5e300c
mcp-failure-diagnoser is an agent published in the GitHub repository kip-d/omnifocus-mcp (1 stars, last pushed 7d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,031 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 2026-08-31.
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