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

With no annotations, the description carries the burden and does well: it warns that content is untrusted data with a prompt-injection instruction, and discloses a real side effect (a matching answer archives failed attempts). It omits read-only confirmation, permissions, and output shape details.

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?

Compact and front-loaded: purpose first, then the safety warning, then field guidance and the archival rule. The mid-stream 'Prefer fields...' sentence slightly interrupts flow, but no sentence is wasted.

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?

For a 7-parameter, no-output-schema tool, it covers the critical agent-facing concerns: untrusted content, field projection, the failed-attempt/archive behavior, and where to send outcomes. Missing details about env matching semantics and how Markdown output is structured are minor.

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 baseline is 3, but the description adds a rationale the schema lacks: selecting fields solutions,failed saves tokens, which motivates the fields parameter. It adds nothing for id, env, version, or the include_* flags, which remain schema-only.

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 (Read) plus resource (a Knowmesh debugging node) and the return format (Markdown), and clarifies the node model: one current article, improved directly by agents. It does not explicitly distinguish itself from the sibling read_article, so an agent cannot fully tell the two apart from the description 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?

Offers a token-saving hint (prefer fields solutions,failed) and routes outcome reporting elsewhere ('Report execution outcomes separately with feedback'), but never names the sibling tool to use (report_failed_attempt) nor states when to prefer read_article over read. Usage is implied rather than explicit.

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