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Get recipe (markdown)

get_recipe
Read-only

Read one recipe: returns the current version as markdown (title, one-paragraph answer, url, version, last updated, report count and score status, then inputs, steps, pitfalls and success criteria). Use it after ask_how_to or search_recipes gave you a slug. Read-only, no key, no obligation; use download_recipe instead if you commit to try it and file a scored report, or get_recipe_details for versions and past reports as JSON. Unknown slug returns an error. After trying the recipe, quick_report(slug, outcome) so it improves; failures count too.

Input Schema

NameRequiredDescriptionDefault
slugYesRecipe slug from ask_how_to or search_recipes, e.g. 'daily-inbox-triage'

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / slug / description
      Added value: +"Recipe slug from ask_how_to or search_recipes, e.g. 'daily-inbox-triage'"
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=false, and the description adds genuinely new context: no key required, no obligation, and that an unknown slug returns an error. It stops just short of discussing caching, rate limits, or whether versions change between reads. Note the closing line mixes a quick_report instruction in, but it is not a contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose and return contents are front-loaded in the first sentence, with routing and follow-up instructions after. The parenthetical field list is dense but earns its place by substituting for a missing output schema; the final quick_report clause is slightly tangential but still useful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description compensates by listing the returned sections (title, answer, url, version, last updated, report count, score status, inputs, steps, pitfalls, success criteria). Combined with the error behavior and sibling routing, an agent has everything needed to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the single slug parameter already carries its own description with an example, so the description's mention of the slug adds nothing new. Baseline 3 is appropriate when the schema does all the work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource (read one recipe) and enumerates the returned content fields, so the agent knows exactly what comes back. It is clearly distinguished from siblings like get_recipe_details (JSON versions/reports) and download_recipe (commitment + reporting).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says to use it after ask_how_to or search_recipes produced a slug, and names two alternatives with their selecting conditions: download_recipe when committing and filing a report, get_recipe_details for versions and past reports as JSON. It even prescribes the post-read follow-up, quick_report(slug, outcome), including failures.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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