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Jrains-ux

code-context-storage-mcp

by Jrains-ux

knowledge_confirm

Confirm a knowledge entry in a code context knowledge base after an operation, using evidence references and actor details to validate the recorded fact.

Instructions

knowledge confirm

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actorYes
reasonNo
request_idNo
knowledge_idYes
operation_idYes
tool_versionNo
evidence_refsNo
schema_versionNo
permission_scopeNo
Behavior1/5

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It reveals nothing about what happens when the tool is invoked, what side effects occur, what permissions are required, or what the response format is. For a tool that implies a confirmation action, this is a significant gap, leaving the agent completely in the dark.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

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

The description is extremely short, which might appear concise, but it lacks any substantive content. This is under-specification rather than conciseness; the single phrase adds no value and does not front-load any useful information. A minimal but helpful description would at least state the tool's purpose and key behavior.

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

Completeness1/5

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

Given the tool's complexity—9 parameters, no annotations, no output schema—the description is woefully incomplete. It provides no context about the operation, when to use it, what the expected inputs mean, or what the agent should expect as a result. This is drastically insufficient for correct invocation.

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

Parameters1/5

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

The schema has 9 parameters with 0% description coverage, and the description adds nothing. It does not explain the meaning of critical fields like knowledge_id, operation_id, or evidence_refs, nor does it describe how parameters interrelate. The description is entirely unhelpful for parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose1/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description is simply 'knowledge confirm', which repeats the tool name and gives zero information about what the tool actually does. It does not state a verb-resource pair or differentiate from siblings like knowledge_reject or confirm. This is a textbook tautology, providing no additional substance beyond the name itself.

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

Usage Guidelines1/5

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

There is no guidance on when to use this tool versus alternatives such as knowledge_reject, confirm, or semantic_confirm. The description offers no context, prerequisites, or exclusion criteria. An agent has no basis to decide if this is the right tool for a given task.

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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