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adithya-1010010

COS-MCP

analyze_knowledge_risk

Read-only

Calculate bus factor per team to identify knowledge silos, sole owners of critical systems, and single points of failure, helping assess organizational continuity risk.

Instructions

Analyze organizational knowledge risk by calculating bus factor per team. Identifies sole owners of critical systems, undocumented services, and single points of failure. Use this when you need to assess continuity risk, identify knowledge silos, or determine which teams are most vulnerable to employee departure.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scopeNoScope of analysis: "team" for one team, "department" for related teams, "organization" for all teamsorganization
teamIdNoFilter analysis to a specific team ID
Behavior3/5

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

The readOnlyHint annotation already communicates that this is a safe read operation. The description adds useful context about the risk indicators it identifies, but does not disclose output format, return structure, or data dependencies. This is adequate given annotations, but not rich.

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 two sentences, front-loaded with the main verb and resource. It has no redundant phrases and every sentence adds substantive information, making it highly concise and well-structured.

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?

The description effectively covers what the tool does and when to use it. With no output schema, it could be improved by stating the return format, but the simple parameter set, optional inputs, and read-only nature make it sufficiently complete for an agent.

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?

Schema description coverage is 100%, so the parameters are well-documented and the baseline is 3. The description does not add much beyond the schema, though it implies team-level analysis; it does not explain interaction between scope and teamId, but the schema already clarifies this.

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 defines the tool's purpose: analyzing organizational knowledge risk by computing bus factor per team and identifying specific risk indicators like sole owners and single points of failure. This differentiates it from sibling tools such as 'calculate_bus_factor' by positioning a broader risk analysis scope.

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 provides explicit use cases: assessing continuity risk, identifying knowledge silos, and determining team vulnerability to departure. However, it does not include exclusions or mention when to prefer alternative tools, so it falls short of full guidance.

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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