Server Quality Checklist

Tool Scores

• hasdata_instagram_profile_getInstagramProfileA
  3.7/5.0
  Behavior3/5

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

  There are no annotations, so the description must carry the burden of behavioral disclosure. It states it fetches public data and lists the returned fields, which is helpful. However, it omits potential rate limits, error behavior, or whether data is live or cached. For a read operation it is adequate but not thorough.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is concise and well-structured: it states the action, lists return fields, then adds use cases. It is front-loaded with the core purpose and each sentence earns its place. Slight trimming of use cases could tighten it, but it remains focused.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  The tool is simple with one parameter and no output schema. The description covers what it returns, effectively acting as output documentation. It does not discuss failure modes, but for a basic GET that is acceptable. Overall it is complete for its complexity.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The only parameter, handle, is fully described in the schema (username without @). The description repeats that it's a handle but adds nothing beyond the schema. With 100% schema description coverage, the baseline of 3 is appropriate.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool fetches a public Instagram profile by handle and enumerates the specific data returned (full name, bio, follower counts, flags, etc.). It is distinct from the sibling posts tool, though it does not name it. The verb and resource are explicit, making the purpose unambiguous.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description lists concrete use cases (CRM enrichment, influencer verification, competitor monitoring, dataset building), giving context for when to use it. However, it does not explicitly compare to the sibling posts tool or state when not to use it. It provides guidance but lacks exclusion criteria.

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

• hasdata_instagram_posts_getInstagramPostsA
  3.8/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden. It discloses the read-only nature (fetches), the pagination mechanism via nextPageToken, and limits to public accounts, which is good. However, it does not explicitly state that it performs no mutations, nor does it mention auth requirements, rate limits, or error behavior (e.g., private account handling). These gaps are notable given the absence of annotations.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness3/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is moderately sized but includes a redundant title phrase ('Get Instagram Posts') that repeats the tool name. It also lists fields in a long enumeration, which is informative but not strictly necessary for operation. It is front-loaded with the main action, but the structure could be tightened without losing value.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given no output schema, the description sufficiently explains the return payload (post fields, media, account info) and pagination. It covers all parameters and provides usage context. Missing details are mostly error conditions or authentication specifics, which are not critical for a simple GET operation. Overall, it is complete enough for an agent to call it correctly.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema coverage is 100%, so the schema already documents each parameter clearly. The description adds marginal value by reinforcing the pagination token's purpose and the handle format (without '@'), but it does not provide semantic details beyond the schema's own descriptions. Baseline 3 is appropriate when schema handles parameter explanation.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the verb ('Get') and resource ('Instagram Posts'), specifies the input (username/handle), and enumerates the exact return fields (caption, hashtags, mentions, counts, URLs, etc.) plus account info. This distinguishes it from the sibling tool (profile get) by resource focus, making the purpose unambiguous.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  It provides explicit use cases ('monitor competitor content', 'track engagement', 'build datasets') and contextual guidance for when to use this tool. However, it does not mention any exclusions or direct alternatives (like the sibling for profile data), so it misses the full 'when-not-to-use' guidance.

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