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feature-tracker-mcp

feature-tracker-mcp

by spe-investigator
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

study_open

Open an investigation that produces a document and a decision, not code. Use when a question needs real analysis before building anything.

Instructions

Open an investigation whose deliverable is a document and a decision, not code. Use when a question needs real analysis before anything can sensibly be built — whether an effect is real, which of two designs survives contact with the data, whether something is worth doing at all. A study is NOT a feature: it has no acceptance criteria, and it may correctly conclude 'do not build this'.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "question": "<question>"
    },
    "name": "study_open"
  }
}

Input Schema

NameRequiredDescriptionDefault
cwdNoDirectory identifying the project and the tree. Defaults to this session's working directory, which in a git worktree is that worktree.
actorNo
contextNoWhat prompted it, and what decision waits on it.
questionYesThe question, stated so it can actually be answered.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It usefully explains conceptual behavior: the deliverable is a document and decision, not code; there are no acceptance criteria; it may conclude 'do not build this'. However, it does not state side effects such as whether a study record is created, what state it enters, what the call returns, or any follow-up needed. This is a noticeable gap for a creation action.

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 tight and front-loaded: purpose first, then usage conditions, then an explicit exclusion. Every sentence earns its place, and there is no redundant filler or restating of the tool name.

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?

Because there is no output schema and no annotations, the description should explain return behavior and effects, but it does not. It gives strong conceptual framing and usage context, yet omits operational details like what a successful open returns and how it connects to study_design/study_status. For a creation command, that leaves an agent with some uncertainty about what to expect.

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 75%, covering cwd, context, and question, while actor is undescribed. The description adds no per-parameter detail, though it does reinforce that 'question' must be genuinely answerable through analysis. It does not compensate for the undocumented actor parameter or provide syntax or format guidance beyond the schema.

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 and resource: 'Open an investigation', and immediately defines the deliverable as 'a document and a decision, not code'. It explicitly contrasts with feature work, which helps differentiate it from feature_propose and other build-oriented siblings. Among the study_* tools, 'open' clearly signals the creation action.

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 explicitly says 'Use when a question needs real analysis before anything can sensibly be built' and gives concrete examples of such questions. It also provides an exclusion: 'A study is NOT a feature' with criteria that distinguish when this tool is inappropriate. This effectively routes the agent away from feature tools without needing to open their schemas.

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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