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

With no annotations, the description carries the full burden. It indicates a read-style operation ('Load') and names what is loaded, but does not disclose return format, error behavior, authentication needs, or whether linked evidence is embedded or referenced.

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 a single, focused sentence with no filler. It front-loads the action and resource, and every word earns its place.

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 get operation, the description covers the core purpose and scope. However, with no output schema and no annotations, it omits return details and failure semantics, leaving some ambiguity about what the agent will receive.

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. It mentions 'one GitHub repository' but does not explain that owner and name identify the repository or clarify their roles. The parameter names are self-explanatory, but the description adds little semantic value 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 uses a specific verb ('Load') and identifies the exact resource ('AtlasRepo decision record and linked evidence') scoped to 'one GitHub repository'. This clearly distinguishes it from the sibling tools, which are about recommending and 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?

The description clearly implies use when a specific repository's decision record is needed, and the 'one GitHub repository' scope distinguishes it from search-oriented siblings. However, it does not explicitly state when not to use it or mention alternatives.

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 provided, the description carries the behavioral disclosure burden. It tells the agent that recommendations are evidence-backed and that outputs are repositories/workflows, but it does not explain how recommendations are produced, what limits or failures may occur, or any caveats about the evidence sources.

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 a single, focused sentence that front-loads the key action and output. There is no filler, repeated boilerplate, or unnecessary structure.

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 simplicity of the tool (two parameters, no nested objects, no output schema), the description provides adequate context for invocation: input is a problem statement, output is repositories/workflows. It could be more complete by describing the result format or evidence presentation, but the core usage is readable.

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 input schema already covers both parameters well (100% coverage), giving a baseline of 3. The description adds extra meaning by making clear that the query should be a concrete engineering or content-production problem rather than a generic keyword lookup, which helps an agent phrase the query effectively.

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 ('find') with a clear resource ('repositories and workflows') and a clear target scenario ('a concrete engineering or content-production problem'). It communicates the tool's function well, though it does not explicitly contrast against sibling tools like atlasrepo_search_tools or atlasrepo_get_repository.

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 a clear use context: use this when you have a concrete problem or outcome and want evidence-backed repository/workflow recommendations. It does not provide when-non-to-use guidance or explicitly name alternatives, so it stops short of a top score.

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 must carry the full behavioral burden. It only states the action and filters; it does not disclose whether the operation is read-only, how results are ordered, whether pagination exists, or what the response shape looks like. For a search tool, one might expect a statement like 'returns a list of matching tools,' but that is absent.

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 a single sentence with no filler. It front-loads the action and lists the three filtering dimensions in a compact, scannable way. Every word carries meaning, and there is no redundant phrasing.

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?

The tool is relatively simple (3 optional params, no output schema). However, given that siblings exist and no output shape is defined, the description leaves out what the search returns (list? count? tool objects?) and any caveats (e.g., empty query behavior). It is adequate for a basic search but not fully complete for an agent that needs to interpret results.

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 100%, so each parameter already has explicit meaning (free-text, kind/category, quality between 0 and 1). The description merely names these in prose ('text, kind, and quality threshold') without adding new semantics like how the kind field matches (exact? partial?) or how minQuality interacts with the score. This meets the baseline for full schema coverage but does not exceed it.

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 states a specific verb ('search'), a specific resource ('normalized open-source tools'), and the key filtering dimensions (text, kind, quality threshold). This clearly distinguishes it from its siblings 'atlasrepo_recommend' and 'atlasrepo_get_repository' — one suggests tools, the other fetches a single repository. The agent can immediately tell what this tool does.

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 gives no context on when to choose this tool over its siblings. It does not mention that 'atlasrepo_recommend' is for getting curated suggestions or that 'atlasrepo_get_repository' returns details for a specific repo. An agent would have to infer that 'search' is for finding tools by criteria, but no explicit guidance or exclusions are provided.

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