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update_project_knowledge

DestructiveIdempotent

Replace a project's knowledge (up to 20,000 characters) — the standing notes the AI builder reads on every change. This replaces the whole text, so read it with get_project_knowledge first and send the edited version.

Input Schema

NameRequiredDescriptionDefault
idYesProject UUID
contentYesThe full knowledge text

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true and idempotentHint=true, but the description adds the key missing detail: it replaces the WHOLE text, not a partial edit, and therefore requires a read-modify-write cycle to avoid data loss. It also states the 20,000-character ceiling. It stops short of describing what happens on failure or whether prior versions are recoverable, so not 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tightly written sentences. The destructive whole-replacement semantics are front-loaded, and the read-first workflow follows immediately. Every clause carries 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 two-parameter tool with full schema coverage, no output schema, and annotations covering the safety profile, the description supplies exactly the missing pieces: what the resource means and the mandatory read-before-write sequence.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so both parameters are documented; the baseline is 3. The description adds genuine semantics by clarifying that 'content' must be the entire replacement text rather than a delta, which changes how an agent constructs the argument.

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?

Specific verb 'Replace' plus the resource 'project's knowledge', and it goes further by explaining what that resource is ('the standing notes the AI builder reads on every change'). This lets an agent distinguish it from get_project_knowledge, which it names explicitly, without opening either schema.

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?

Explicit workflow instruction: read with get_project_knowledge first, then send the edited version. It names the sibling to use for the read step and describes the exact sequencing, leaving nothing to inference.

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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