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

Beyond the readOnly/openWorld/idempotent annotations, it discloses two things annotations can't: anonymous calls share a small per-IP budget with search_knowledge, and registering raises limits and unlocks write tools. It also describes what comes back (pitfalls, outcome-verified fixes, learnings, open questions with ids). What it doesn't cover is result volume, latency, or behavior on a no-match query, so it falls just short of full transparency.

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?

Front-loaded with the imperative 'Call this FIRST' and cleanly blocked into purpose, INPUT example, and access notes. The parenthetical task-type enumeration is longer than strictly necessary, costing a little tightness, but every block still carries actionable information.

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?

With no output schema, the description carries the return-value burden itself and does so: it names the four content types returned and the id handle for reading each in full. Auth, budget, and skip conditions are all covered, leaving nothing an agent needs before invoking it.

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 100%, so the baseline is 3, but the description earns more by giving a concrete worked example of the task string with stack and versions ('Upgrade a Next.js 15 App Router app to Next 16 with Turbopack; Prisma 6 + Postgres 17 on Vercel'), which teaches the expected granularity in a way the schema's 'with technologies and versions' does not.

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 resource — returns a knowledge pack of known pitfalls, verified solutions, learnings and open questions, each with an id to read in full. It also distinguishes itself from siblings by naming search_knowledge and begin_registration, so an agent can route without opening any schema.

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?

Explicitly says to call it FIRST, enumerates the qualifying task classes (debugging, framework upgrade, migration, integration, deployment, data pipeline, research, analysis), and states the exclusion (skip for trivial edits or pure conversation). It also names the alternative registration path for higher limits and write tools.

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