june_enrich

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

With no annotations provided, the description fully discloses behavioral traits: idempotent (second run writes 0 new), runs as a background job, returns 409 if already running, 403 on free endpoints, and the return format. This exceeds the burden.

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?

The description is compact and front-loaded with the key action. However, it packs a lot of information into a dense single paragraph, which could be slightly restructured for readability without losing content.

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?

Given the absence of an output schema and annotations, the description provides a complete picture: purpose, when to use, how to use, idempotency, error codes, expected return format ({job_id, state, total, processed, nodes, edges, errors}). Nothing is left ambiguous.

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?

The schema has 0% description coverage, leaving the description to explain parameters. It clearly explains the sole optional parameter 'job': call with no args to start, then pass {job: <job_id>} to check progress. This adds essential meaning beyond the schema.

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?

The description clearly states the tool's purpose: re-extracting existing artifacts with a richer engine as a background job. It distinguishes itself from siblings like june_remember by specifying use cases (after Pro upgrade or many june_remember writes). The verb 're-extract' and resource 'this canvas's existing artifacts' are specific and unambiguous.

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?

The description provides explicit guidance on when to use the tool: after a Pro upgrade to backfill memories, or after many june_remember writes. It also explains idempotency and how to start (no args) vs. check progress (with job argument). This clearly differentiates from alternatives.

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