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

With no annotations, the description carries the full burden. It does disclose two useful behaviors: the return is the full text (not a summary or metadata), and only approved documents are eligible. It says nothing about what happens for unapproved or missing doc_ids, size/truncation limits on full text, or required permissions.

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?

A single sentence with no padding. The resource and the scoping constraint (full text, approved, single document) come before the parameter detail, so it is properly front-loaded.

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 one-parameter read tool with no output schema and no annotations, the description covers the essentials: what it returns (full text), which documents are eligible (approved), and the key format. The remaining gap is failure behavior for unapproved or unknown IDs, which is minor but not negligible given the explicit "approved" qualifier.

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%, so the lone doc_id parameter is undocumented in structured data. The description partially compensates by giving a concrete format example (MHB-OPS-001), but it does not say where an agent obtains a valid doc_id or whether other identifier schemes are accepted.

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?

"Fetch the full text of one approved document by doc_id" gives a specific verb (fetch), a specific resource (full text of a document), and the exact key parameter. It implicitly contrasts with the retrieval-by-search sibling, but never names search_knowledge or list_sources, so differentiation from siblings is left to inference.

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 word "approved" hints at a precondition, and "by doc_id" implies the identifier must already be known, which suggests this is a follow-up to search_knowledge. However, there is no explicit statement of when to use this versus search_knowledge, nor any stated exclusion or prerequisite.

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

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

No annotations are provided, so the description carries the full burden. It does disclose a meaningful behavioral trait — results are permission-filtered to 'approved documents the current caller is allowed to see' — which is real value beyond the schema. However, it says nothing about ordering, pagination, result size, or what an empty result means, leaving key runtime behavior undocumented.

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?

A single sentence with no filler, and the core scope constraint (caller visibility) sits at the end of an already short clause. Nothing could be removed without losing 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?

For a zero-parameter list tool with no output schema, the description tells the agent what is returned (approved, caller-visible documents) and implicitly why the set may be smaller than the full corpus. The only shortfall is the absence of any note on result volume or pagination, which matters when there is no output schema to describe shape.

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 tool takes zero parameters, so the baseline is 4; there is nothing for the description to clarify beyond the bare schema. It does not introduce any phantom parameters or misleading filter language, which keeps it clean.

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 uses a specific verb ('List') with a specific resource ('approved documents') and adds a scope qualifier ('the current caller is allowed to see'). It is clear enough to distinguish from get_document by implication (plural enumeration vs single retrieval), but it never names search_knowledge or explains how this differs from searching.

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?

Usage is only implied: the word 'List' suggests a browsing/discovery scenario, but there is no explicit statement of when to call this instead of search_knowledge, and no exclusions or preconditions are given. An agent must infer the routing decision from the verb alone.

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

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

With no annotations, the description carries the full burden, and it does disclose the return shape (doc_id, title, version, classification, citation) plus a hard constraint that top_k is capped at 10. It stops short of noting permission requirements or whether unapproved content is silently excluded versus erroring, which matters for a knowledge-retrieval tool.

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, front-loaded sentences with no filler; purpose comes first and the constraint is placed at the end where it is easy to scan. Slightly clipped phrasing ('version, classification and a citation') costs a little clarity but no words are 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 simple two-parameter read tool with no annotations and no output schema, the description covers purpose, return fields, and the key limit. The remaining gap is query semantics and the absence of any retrieval-failure behavior, which keeps it just short of complete.

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%, so the description must compensate for both parameters. It explains only top_k, and only partially — the cap of 10 is useful but it never states that top_k is the number of results returned, and the query parameter's expected syntax or matching behavior is never described.

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 gives a specific verb and resource ('Search approved internal knowledge') with a meaningful scope qualifier ('approved'). It implicitly separates itself from get_document by promising 'snippets' rather than full documents, but never names that sibling or states the distinction explicitly.

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 use case is implied by 'snippets' and the approved-content scope, so an agent can infer this is for lookup rather than document retrieval. However, there is no explicit when-to-use guidance and no mention of get_document or list_sources as alternatives.

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