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aidesignblueprint

AI Design Blueprint Doctrine

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me.add_evidence

Add a concrete evidence note to a specific course stage, recording implementation observations, decisions, or artefacts that demonstrate progress through a Blueprint principle. Persisted per user and course.

Instructions

Authenticated — append a free-text evidence note to a specific stage in the caller's active course. Notes record concrete implementation observations, decisions, or artefacts that demonstrate progress through a Blueprint principle (e.g. how a delegation boundary was implemented, what approval flow was chosen and why). Persisted as UserStageEvidence rows scoped to (user_id, course_slug, stage_slug). WHEN TO CALL: AFTER the user has articulated something concrete they have built, observed, or decided — not to capture intent or speculation. Pair with me.coaching_context to close evidence gaps. WHEN NOT TO CALL: to log every conversation turn; to record planning, ideas, or todos; on behalf of another user; without the user's awareness (they should know their progress is being recorded). BEHAVIOR: write-only, single insert. Auth: Bearer (Firebase ID token, any plan). UK/EU residency. Notes are visible only to the owning user and are surfaced on me.learning_path / me.coaching_context. Confirms the stage_slug + course_slug pair in the response so the user can see which stage was credited.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteYesEvidence note to append to the delegation boundary notes for this stage.
stage_idYesID of the stage to append the evidence note to.
course_slugYesSlug of the course the stage belongs to (e.g. 'agentic-fundamentals').

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Annotations indicate readOnlyHint=false, and the description adds behavioral details: 'write-only, single insert', auth requirements (Bearer token), residency (UK/EU), and visibility scope (visible only to owning user). No contradiction with annotations.

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?

The description is well-structured with sections and front-loaded purpose, but slightly lengthy. Every sentence adds value, so it earns a high score.

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?

For a tool with 3 parameters and an output schema, the description covers usage, behavior, auth, scope, and response details comprehensively.

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

Parameters5/5

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

Schema coverage is 100%, and the description enriches parameters by explaining that notes record concrete observations, persistence as UserStageEvidence rows, and confirmation of stage_slug + course_slug in response.

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 clearly states the tool's purpose: 'append a free-text evidence note to a specific stage in the caller's active course.' It uses a specific verb (append) and resource (evidence note to a stage), and distinguishes from sibling tools like me.coaching_context.

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?

Includes explicit 'WHEN TO CALL' and 'WHEN NOT TO CALL' sections, specifying that it should be called after concrete observations, not for intent or speculation, and not for every conversation turn. Also mentions pairing with me.coaching_context.

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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