AI PM Lab

Prepare for an AI planning meeting

prep_planning_meeting

Read-onlyIdempotent

The questions a PM should ask engineers about a planned AI feature, with why each matters and what a good answer sounds like. Returns instructions to follow with the user's text.

Input Schema

Name	Required	Description	Default
`feature`	No	A few sentences about the AI feature

Output Schema

Name	Required	Description	Default
`text`	Yes	The answer in markdown, as shown to the user; for the guides, instructions to follow with the user's text
`links`	Yes	The AI PM Lab pages the answer links to, where each idea can be tried hands-on

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 12, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": false,
+  "properties": {
+    "links": {
+      "description": "The AI PM Lab pages the answer links to, where each idea can be tried hands-on",
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "text": {
+      "description": "The answer in markdown, as shown to the user; for the guides, instructions to follow with the user's text",
+      "type": "string"
+    }
+  },
+  "required": [
+    "text",
+    "links"
+  ],
+  "type": "object"
+}

First observedOct 10, 2026

TDQS

B3.4/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so safety is covered. The description adds genuinely useful non-obvious context: the tool returns instructions to follow rather than a direct answer, which shapes how the agent should consume and act on the result. It does not cover edge cases or what happens with empty input, keeping it below a 5.

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?

Two short sentences with no filler. The first sentence front-loads the content of the result, though the trailing 'Returns instructions to follow with the user's text' is slightly ambiguous and reads as an afterthought.

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?

For a single-parameter read-only tool with an output schema and full annotation coverage, the description is adequate: return values need not be explained and safety is handled. The notable gap is situational framing – when this should be chosen over sibling planning tools – which leaves the agent to guess placement in a workflow.

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?

With a single parameter at 100% schema coverage, the schema already documents 'feature' as a few sentences about the AI feature. The description's phrase 'a planned AI feature' and 'the user's text' loosely align with that parameter but add no syntax, length, or format detail beyond the schema. Baseline 3 applies.

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

Purpose4/5

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

The description names a specific artifact it produces – the questions a PM should ask engineers about a planned AI feature, with rationale and example good answers – which is more concrete than the name alone. It stops short of distinguishing itself from planning-adjacent siblings such as plan_ai_launch or review_ai_spec, so it is clear but not sibling-routing.

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?

There is no when-to-use or when-not-to-use guidance and no named alternative among the many overlapping planning/review siblings. The agent must infer the moment to call this from the title alone.

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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