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AI Design Blueprint

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by aidesignblueprint
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Python
Remote

signals.feedback

Capture explicit user feedback on Blueprint surfaces, recording what helped and what's missing, with optional contact email only when follow-up permission is granted.

Instructions

Public — records explicit free-text user feedback about the Blueprint, this tool surface, or a specific principle/example. Captures category (bug, doctrine_critique, missing_example, ergonomics, other), free-text body, and optional contact_email when permission_to_follow_up is true. WHEN TO CALL: ONLY when the user explicitly says they want to give feedback (e.g. 'can you log this as feedback', 'file this critique', 'send a bug report'). Use signals.report instead for value-moment metrics (rating validate's output 1-5). WHEN NOT TO CALL: proactively, silently, or to substitute for signals.report. Never harvest contact info without explicit permission_to_follow_up=true. BEHAVIOR: write-only, no auth required (open to all callers). Stores one feedback record, at rest under UK/EU residency. contact_email is stored ONLY when permission_to_follow_up=true, and that fact is confirmed back in the response so the user can see the privacy boundary. When permission_to_follow_up=true AND a valid contact_email is given, and only then, it also opens a support inbox item so a human can reply, and the free-text fields are sent to OpenAI for triage (severity and a short summary). The contact_email field is never part of that request, so keep personal data out of the free text. In every other case nothing leaves the server.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
surfaceNoWhich Blueprint surface the feedback is about. Use 'mcp' if the session was via Claude Code or another MCP client. Use 'principles', 'examples', 'guides', 'coaching', or 'validation' based on what the user interacted with.
task_typeNoWhat the user was doing when they decided to give feedback. Use plain English — e.g. 'code-review', 'architecture-design', 'agent-setup', 'onboarding', 'validation'. Infer from context.
what_helpedNoAsk the user: 'What was most helpful?' Record their answer verbatim or paraphrased in plain English. Max 1000 chars. No code snippets, no proprietary content.
what_missingNoAsk the user: 'What was missing or could be improved?' Record their answer verbatim or paraphrased. Max 1000 chars.
contact_emailNoOnly ask for this if the user explicitly says they want a follow-up response. Never prompt for email unprompted. Only stored when permission_to_follow_up=true.
rating_clarityNoAsk the user: 'How clear was the Blueprint guidance? Rate 1–5.' 1 = very unclear, 5 = very clear. Only set if the user gives an explicit number.
would_use_againNoAsk the user: 'Would you use the Blueprint again for a similar task?' Set true/false based on their answer. Only set if they answer explicitly.
rating_usefulnessNoAsk the user: 'How useful was the Blueprint for this task? Rate 1–5.' 1 = not useful, 5 = very useful. Only set if the user gives an explicit number.
permission_to_follow_upNoSet to true only if the user explicitly said they want a follow-up. Must be confirmed before storing contact_email.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.2.0
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "title": "submit_feedbackDictOutput",
+  "type": "object"
+}
  2. Changed10 schema fields changedv1.1.0
    • changedInput schema / properties / contact_email / description
      Previous value: -"Email address for follow-up. Only stored when permission_to_follow_up is true."New value: +"Only ask for this if the user explicitly says they want a follow-up response. Never prompt for email unprompted. Only stored when permission_to_follow_up=true."
    • changedInput schema / properties / permission_to_follow_up / description
      Previous value: -"Set to true to grant permission to store contact_email and receive a follow-up response."New value: +"Set to true only if the user explicitly said they want a follow-up. Must be confirmed before storing contact_email."
    • changedInput schema / properties / rating_clarity / description
      Previous value: -"Clarity rating from 1 (very unclear) to 5 (very clear)."New value: +"Ask the user: 'How clear was the Blueprint guidance? Rate 1–5.' 1 = very unclear, 5 = very clear. Only set if the user gives an explicit number."
    • changedInput schema / properties / rating_usefulness / description
      Previous value: -"Usefulness rating from 1 (not useful) to 5 (very useful)."New value: +"Ask the user: 'How useful was the Blueprint for this task? Rate 1–5.' 1 = not useful, 5 = very useful. Only set if the user gives an explicit number."
    • changedInput schema / properties / surface / description
      Previous value: -"Surface or feature the feedback is about (e.g. 'principles', 'examples', 'mcp', 'coaching')."New value: +"Which Blueprint surface the feedback is about. Use 'mcp' if the session was via Claude Code or another MCP client. Use 'principles', 'examples', 'guides', 'coaching', or 'validation' based on what the user interacted with."
    • changedInput schema / properties / task_type / description
      Previous value: -"Type of task the user was doing (e.g. 'code-review', 'architecture-design', 'onboarding')."New value: +"What the user was doing when they decided to give feedback. Use plain English — e.g. 'code-review', 'architecture-design', 'agent-setup', 'onboarding', 'validation'. Infer from context."
    • changedInput schema / properties / what_helped / description
      Previous value: -"What was most helpful. Max 1000 chars."New value: +"Ask the user: 'What was most helpful?' Record their answer verbatim or paraphrased in plain English. Max 1000 chars. No code snippets, no proprietary content."
    • changedInput schema / properties / what_missing / description
      Previous value: -"What was missing or could be improved. Max 1000 chars."New value: +"Ask the user: 'What was missing or could be improved?' Record their answer verbatim or paraphrased. Max 1000 chars."
    • changedInput schema / properties / would_use_again / description
      Previous value: -"Whether the user would use the Blueprint again for a similar task."New value: +"Ask the user: 'Would you use the Blueprint again for a similar task?' Set true/false based on their answer. Only set if they answer explicitly."
    • changedOutput schema / (root)
      Previous value: -{
-  "additionalProperties": true,
-  "title": "submit_feedbackDictOutput",
-  "type": "object"
-}New value: +null
  3. First observedv1.0.0

TDQS

A4.9/5.0
Behavior5/5

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

The description goes far beyond the annotations. It discloses that the tool is write-only and open to all callers, stores data under UK/EU residency, only stores contact_email when permission_to_follow_up=true and confirms that back to the user, opens a support inbox item and sends free-text to OpenAI for triage only under specific conditions, and explicitly says personal data must stay out of free text. This is rich, actionable behavioral 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?

The description is long but well-structured with clear sections (purpose, when to call, when not to call, behavior). It is front-loaded with the core purpose and each sentence adds necessary information. No fluff; every detail about privacy and data handling earns its place.

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?

Given the complexity of 9 optional parameters and the presence of an output schema, the description covers all essential aspects: when to call, privacy boundaries, data residency, external processing, and the distinction from signals.report. Nothing an agent needs to correctly invoke the tool is missing. The output schema handles return values, so the description need not explain them.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds value by explaining the conditional relationship between permission_to_follow_up and contact_email, and by warning to keep personal data out of free text. It also clarifies that category is captured, though the schema already lists it. This is more than the schema provides, so a 4 is warranted.

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 states a specific verb ('records') and a specific resource ('explicit free-text user feedback about the Blueprint, this tool surface, or a specific principle/example'). It also explicitly differentiates from the sibling signals.report by saying 'Use signals.report instead for value-moment metrics', so an agent can distinguish between the two without opening schemas.

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?

The description contains explicit 'WHEN TO CALL' and 'WHEN NOT TO CALL' sections. It specifies that the tool should only be called when the user explicitly requests feedback, gives concrete examples, names the alternative (signals.report) and the condition for it, and warns against proactive or silent use. This is unambiguous guidance.

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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