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by io.github.Onplana
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analyze_project_risks

Destructive

Run AI risk analysis on one project and merge the findings into its risk register (visible via list_risks). A finding that matches an open AI risk nobody has touched updates it; one matching a risk a person or agent added or edited, or a dismissed risk, is skipped; the rest are added. Nothing is removed. Use this when the user asks "what could go wrong on Project X" or before a sprint planning meeting. Caller needs write access to the project, as for create_risk.

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": {
      "projectId": "<projectId>"
    },
    "name": "analyze_project_risks"
  }
}

Input Schema

NameRequiredDescriptionDefault
projectIdYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

Goes well beyond the annotations by spelling out the merge algorithm: untouched open AI risks are updated, human/agent-edited or dismissed risks are skipped, the remainder are added, and nothing is removed. It also states the authorization requirement ('write access to the project, as for create_risk'), which annotations cannot convey.

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?

Three tight sentences, front-loaded with the action and effect, then the merge rules, then the usage triggers. No filler and every sentence carries decision-relevant information.

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

Completeness4/5

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

With no output schema, the description could say what the call returns (counts of added/updated/skipped findings) and whether repeat runs behave the same given idempotentHint=false. Otherwise the mutation semantics, permissions, and triggers are complete enough to call it correctly.

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?

There is one parameter (projectId) with 0% schema description coverage, and the description never says whether it takes an ID, key, or name or where to obtain it. Referencing 'Project X' implies a single project scope but adds no format or lookup guidance, so a gap remains.

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?

States a specific verb and resource ('Run AI risk analysis on one project') and immediately names the effect ('merge the findings into its risk register'), distinguishing it from create_risk and list_risks by describing merge semantics rather than single-entry creation or listing.

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

Usage Guidelines4/5

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

Gives two concrete triggers ('what could go wrong on Project X', before sprint planning) and points at list_risks for viewing and create_risk for the permission model. It stops short of an explicit exclusion (e.g. 'do not use for manually adding a single risk — use create_risk'), so it is strong context rather than full when/when-not routing.

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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