Team Cross-Project Insights

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

Annotations already establish the full safety profile (readOnly, idempotent, non-destructive, closed-world), so the description doesn't need to re-state those. It does add one piece of genuine behavioral context — 'Requires TEAM_DB_PATH' — which is an environment prerequisite not visible anywhere else. However, it says nothing about how the analysis is computed, what 'patterns' means, or any cost/latency implied by scanning all projects.

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

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

Three short sentences, front-loaded with the core purpose, and no filler. It is efficient, though the terseness tips into under-specification rather than pure concision for a tool this analytical.

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

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

An output schema exists, so return values needn't be described, and annotations cover safety. What remains thin is the core promise: 'analyze patterns' is left undefined for a complex cross-project aggregation tool, and the filtering parameters that materially change results go unmentioned.

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

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

Schema coverage is 83%, so the six parameters are largely self-documenting and baseline 3 applies. The description adds nothing about limit, min_entries, the date window, or use_test_db, and in particular never explains how the date range constrains the cross-project analysis.

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

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

States a specific verb and scope: 'Analyze patterns across all GitHub Projects tracked in team entries.' That is far more concrete than a tautology, and 'team entries' hints it operates on the team DB rather than the personal one. It never names the non-team sibling get_cross_project_insights, so the agent must infer the distinction from the 'team' prefix alone.

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

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

'Use for architecture planning' gives a positive use case, which is real but one-dimensional. There is no when-not guidance, no mention of the personal get_cross_project_insights alternative, and no statement of what the agent should use if it wants single-project rather than cross-project data.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.