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find_recipe

Create evidence-based implementation recipes with prerequisites, ordered steps, and validation for coding goals, using target documentation version and project context.

Instructions

Assemble an evidence-grounded implementation recipe with explicit prerequisites, ordered steps, and validation steps.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalYesThe implementation goal or workflow to construct a recipe for.
versionNoTarget documentation version.
projectPathNoWorkspace root for project-aware dependency detection.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.4

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the burden. It does disclose the output shape (prerequisites, ordered steps, validation steps) and the evidence-grounded intent, but it never states whether the tool performs side effects, requires permissions, or how it handles insufficient evidence. It isn't misleading, so this is a passable but not rich disclosure.

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

Conciseness5/5

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

A single, front-loaded sentence. Every phrase contributes a distinct element of the recipe (evidence-grounded, prerequisites, ordered steps, validation steps), with no redundant or filler words.

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

Completeness3/5

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

The description explains the deliverable but omits usage context and exclusions, and with no output schema or annotations it does not fully substitute for them. The three parameters are covered by the schema, and the output is sketched, so the definition is minimally complete but not robust.

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 documentation covers 100% of the three parameters, so the baseline is 3. The description adds no parameter-specific semantics beyond the schema; goal, version, and projectPath are left to their own schema descriptions.

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?

The description opens with a specific verb ('Assemble') and a clear resource ('implementation recipe'), and specifies the recipe's defining components (prerequisites, ordered steps, validation steps). This distinguishes it from sibling doc-lookup tools such as search_docs, find_api, and get_implementation_context, which are about retrieving rather than constructing a plan.

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

Usage Guidelines2/5

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

No guidance is given about when to choose this tool over siblings like find_example, find_pitfall, or get_implementation_context. The description states the function but not the conditions, triggers, or exclusions, leaving the agent to guess situational fit.

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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