netintel_markdown

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

With no annotations, the description carries the full burden. It discloses the underlying model (Claude Haiku) and the transformations applied, which is meaningful behavioral context, but says nothing about input size limits, latency, failure behavior on already-clean or non-HTML input, or whether content is truncated.

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?

One front-loaded sentence that leads with the core action and accumulates useful detail without filler. The trailing ellipsis suggests the text is truncated rather than deliberately ended, which is the only structural flaw.

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 single-parameter transformation with no annotations and no output schema, the description covers purpose and pipeline adequately but omits input expectations, size constraints, and what happens with malformed input. Roughly the minimum an agent needs, with noticeable gaps.

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 description coverage is 0% for the single `text` parameter. The description never clarifies whether it expects raw HTML, a full page document, or plain text, nor whether there is a length cap — the exact gap the schema leaves open. It adds no parameter meaning beyond the name.

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 (Convert) and both the input and output resource (messy HTML/text → clean Markdown), with a concrete processing pipeline (strips boilerplate, fixes heading hierarchy, normalizes lists and links). It is clearly distinguishable from generic siblings like netintel_convert or netintel_normalize, though it never names an alternative tool.

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 trailing clause 'so agents can feed clean docs into downstream' implies a use case, but there is no explicit when-to-use guidance and no exclusion relative to close siblings such as netintel_convert, netintel_extract, or netintel_page_extract. An agent has to infer when Markdown normalization is the right step.

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