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team_knowledge

Retrieve team historical knowledge including failure alchemy, lessons learned, and loop reviews to onboard new agents.

Instructions

Query the team knowledge base — retrieve accumulated experience and lessons learned.

Returns memories with scope=team for this team, including:

  • failure_alchemy: Lessons from failure alchemy

  • lesson_learned: Manually recorded experiences

  • loop_review: Loop review summaries

New Agents should call this tool before joining to get team historical knowledge for quick onboarding.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoType filter, one of failure_alchemy / lesson_learned / loop_review (empty returns all)
limitNoMaximum number of results, default 20
team_idNoTeam ID (leave empty to auto-get active team)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations provided, so description carries full burden. It discloses that it retrieves memories with scope=team and lists the three types (failure_alchemy, lesson_learned, loop_review). This gives the agent a clear picture of what to expect. Does not mention non-destructive nature explicitly, but it's implied.

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 concise: two sentences and a bulleted list. The first sentence clearly states the purpose. The list provides structured details. No superfluous 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?

Given no annotations and presence of an output schema, the description covers everything an agent needs: purpose, return types, filtering options, and onboarding recommendation. It is complete for the tool's complexity.

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 description coverage is 100%, but the description adds context: it explains the meaning of type values ('failure_alchemy: Lessons from failure alchemy') and notes that empty type returns all. It also clarifies team_id can be left empty. This adds value beyond the schema.

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 states 'Query the team knowledge base — retrieve accumulated experience and lessons learned.' It specifies the verb (query/retrieve) and the resource (team knowledge base with specific memory types). Distinguishes from siblings by focusing on team historical knowledge.

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?

Explicitly recommends that 'New Agents should call this tool before joining to get team historical knowledge for quick onboarding.' This provides a clear when-to-use scenario. Does not exclude other contexts, but the guidance is helpful.

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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