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Projectmem

by riponcm
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_instructions

Retrieve the project's mandatory AI instructions at session start to identify workflow rules that must be followed while working. This read-only call does not modify memory.

Instructions

Read the project's mandatory AI instructions.

MANDATORY: call this at session start. The instructions describe the
workflow rules you MUST follow while working in this project — they
are not advisory.

Read-only; does not modify memory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectNoWhich 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
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.3.2
    • 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"
+}
  2. First observedv0.1.1

TDQS

A4.4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It explicitly states 'Read-only; does not modify memory,' which covers the main safety-relevant behavior. It could add more context about what happens if no instructions exist or whether the returned content is cached, but the simple read-only trait is transparently disclosed.

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?

The description is short and front-loaded with the core purpose, followed by the mandatory usage instruction and a read-only safety note. The repetition of 'MANDATORY' and 'MUST' is somewhat redundant, but the text is still efficient and every sentence contributes useful information.

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?

For a simple, low-complexity tool with one optional parameter, a detailed schema, and an output schema, this description is complete. It tells the agent why this tool exists, when it must be called, and that it is side-effect-free. Nothing essential is missing for correct invocation.

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?

The input schema provides 100% coverage of the single optional parameter, including when to omit it and how to resolve a project identifier. The description adds no parameter-specific detail, so baseline 3 is appropriate since the schema already takes care of documenting the parameter fully.

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 clearly identifies the exact action ('Read') and resource ('the project's mandatory AI instructions'), and its emphasis that these are mandatory workflow rules distinguishes it from sibling information tools like get_summary or get_project_map. This is specific, actionable, and immediately tells an agent what the tool is for.

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 commands calling this tool at session start, states that the instructions are not advisory, and makes clear the agent MUST follow the returned rules. This is stronger and more explicit than a mere contextual hint; it tells the agent exactly when and how the tool should be used, leaving no ambiguity.

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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