Projectmem

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get_score

Assess project health by calculating a failure-prevention score, converting past issues into an A+ to F grade with concrete ROI: debugging hours saved, tokens prevented, and dollars protected.

Instructions

Get the project's failure-prevention score.

Returns an A+→F grade with concrete ROI numbers: debugging hours
saved, tokens prevented, dollars protected. Use when the user asks
about progress or value.

Read-only; computes the score from events.jsonl on each call.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`project`	No	Which project this call is about — a registered id, alias, or absolute path (e.g. 'ossdrop'). Omit it when the server was started for a single repo, or when an active project is set with `pjm project use`. Call list_projects to see the registered names.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.3.2Sep 8, 2026

addedInput schema / properties / project

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Which project this call is about — a registered id, alias, or absolute path (e.g. 'ossdrop'). Omit it when the server was started for a single repo, or when an active project is set with `pjm project use`. Call list_projects to see the registered names.",
+  "title": "Project"
+}

First observedv0.1.1May 19, 2026

TDQS

A4.3/5.0

Behavior4/5

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

There are no annotations, so the description carries the behavioral burden. It explicitly says 'Read-only' and 'computes the score from events.jsonl on each call,' which tells the agent the tool is safe and reflects current data rather than cached results. It does not discuss failure modes or file-missing behavior, but for a simple read-only computation the disclosure is strong.

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 three short, purposeful sentences: what it does, what it returns, when to use it, and how it behaves. The most important info is front-loaded, with no filler or repetition of schema details. It is concise without being under-specified.

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 that the output schema exists, the description does not need to explain return shape in detail, yet it already summarizes the grade and ROI components. The optional parameter is fully documented in the schema, and the description covers usage timing and read-only behavior. Nothing essential is missing for an agent to call this tool 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?

Parameter schema coverage is 100%, and the schema description already explains the optional 'project' parameter, its default, when to omit it, and how to discover valid values via list_projects. The tool description adds no new parameter semantics, so the baseline score of 3 is appropriate.

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: 'Get the project's failure-prevention score.' It clarifies what the tool produces (an A+→F grade plus ROI numbers), making it easy to distinguish from siblings like get_summary or get_context. This is more than a tautology and directly supports correct selection.

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?

The description states clearly when to use it: 'Use when the user asks about progress or value.' It does not explicitly name alternative tools or provide when-not-to-use guidance, but the when-to-use condition is concrete and actionable. The read-only note also helps set expectations.

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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