Influship MCP

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by Influship

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.1.1
Disambiguation4/5
Tools are well-disambiguated with explicit usage guidance in each description, contrasting with others. However, some overlap between search_creators and semantic_search_creators remains due to backward compatibility.
Naming Consistency5/5
Tool names follow a consistent verb_noun pattern (e.g., autocomplete_creators, get_creator). Instagram-specific tools use a predictable get_platform_type pattern, with minor variants for plurality.
Tool Count5/5
14 tools is well-scoped for a creator discovery and data retrieval platform, covering search, profile lookup, posts, and matching without being excessive.
Completeness4/5
Covers most creator lifecycle operations (discover, retrieve, match, posts), but lacks cross-platform post retrieval beyond Instagram and advanced analytics tools.
Average 4.5/5 across 14 of 14 tools scored. Lowest: 3.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 6 commits in the last 12 weeks
- Last stable release on May 30, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, but description adds that it retranscribes every request (no caching yet), and mentions caching plans. Adds useful behavioral context beyond annotations.
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?
Concise, with clear first sentence. Second paragraph about caching plans is less essential but not overly verbose.
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 the simple nature of the tool and presence of output schema, the description is fairly complete. Could mention error handling or output format, but covers key behavioral aspect.
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 description coverage is 100% with good descriptions for shortcode and language. The tool description does not add much parameter-specific information, so baseline 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 it transcribes an Instagram video post by shortcode, distinguishing it from siblings like get_instagram_post (post data) and get_instagram_post_transcripts (possibly multiple transcripts).
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?
No explicit guidance on when to use this vs alternatives. Mentions retranscription and caching, giving some context but not clear when-not or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds that it 'retranscribes every request' (no caching) and that successful items include raw post data. This adds useful behavioral context beyond annotations without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no waste. First sentence states core function, second sentence adds a behavioral caveat. Perfectly front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only 2 parameters, 100% schema coverage, and an output schema, the description covers the key aspects: what it does, the bounded nature, retranscribe behavior, and output content. No gaps.
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?
Input schema covers both parameters with descriptions (shortcodes array, language optional). Schema description coverage is 100%, so baseline is 3. The description adds minimal extra meaning beyond 'bounded list' which aligns with the min/max constraints.
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 'transcribe', the resource 'Instagram video posts by shortcode', and the scope 'bounded list'. It distinguishes from siblings like 'get_instagram_post_transcript' (singular) and 'get_instagram_post' (different purpose).
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?
No explicit when-to-use or when-not-to-use guidance. The note 'For now this retranscribes every request' hints at current behavior but doesn't clarify when to prefer this tool over the singular variant or other siblings. Usage context is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and destructiveHint. Description adds value by specifying per-item success/error details and the raw API nature, which helps the agent understand the response structure beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with key action and resource, no redundant information. Every word contributes meaning.
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?
Adequately covers the batch nature and response structure. Could mention the bounded limit (max 20 from schema) but output schema exists so return format is not required. Overall sufficient for this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds context by clarifying the accepted URL patterns (/p/, /reel/, /tv/), which is not obvious from the schema alone. This enhances parameter understanding.
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?
Clearly states verb 'Fetch', resource 'raw Instagram post-page data', and scope 'for a bounded list of shortcodes'. Distinguishes from sibling get_instagram_post (singular) and get_posts (different scope).
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?
Implies batch usage but does not explicitly compare to alternatives like get_instagram_post or state when to use this tool vs others. No exclusion criteria or usage conditions provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate safe read operation (readOnlyHint=true, destructiveHint=false). Description adds value by stating 'Cheap and fast' and describing return format ('short list of matching creators with their IDs, platforms, and display names'). No contradictions.
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?
Well-structured with core action, usage guidelines, examples, and output. Sentences are efficient and front-loaded. Some slight redundancy (e.g., examples repeat the point), but overall concise for the information provided.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of annotations, full schema coverage, and output schema, the description covers purpose, usage, alternatives, examples, and output. It is complete for a tool with moderate 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?
Input schema has 100% coverage; every parameter has a description. Description does not add significant parameter details beyond schema, relying on schema to document parameters. Baseline 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?
Description clearly states 'Autocomplete creator names, usernames, or display names from partial input.' It distinguishes from siblings by explicitly naming alternatives (search_creators, get_profile, semantic_search_creators) and their different use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use ('when the user types a partial handle or name'), when-not-to-use (e.g., 'Use get_profile instead when the user gives an exact platform+username pair'), and names specific alternative tools with rationale.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and destructiveHint, but description adds context beyond annotations: explains how seeds are blended (embeddings), returns ranked list with scores, and mentions pagination via cursor.
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?
Description is front-loaded with bold purpose, uses bullet points and examples. It is reasonably concise, with each sentence adding value. Slightly long but appropriate for a complex tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema, description does not need to document return values. It covers usage context, alternatives, blending method, and pagination. Complete for a tool of this 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?
Schema coverage is 100%, so baseline 3 is appropriate. Description adds some context for seed_profiles (resolve handles via autocomplete_creators) but does not elaborate on all parameters beyond schema definitions.
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?
Description clearly states the tool finds creators similar to seed creators. It uses a specific verb and resource, and distinguishes from siblings by naming alternatives and giving examples.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use (user knows a creator and wants similar) and when not to use (topic/no seed -> semantic_search_creators; specific candidates -> match_creators). Provides concrete examples.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, and description adds behavioral context about fetching fresh data and specific data fields, complementing annotations without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler, front-loaded with action and resource. Every part earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given output schema exists and annotations cover safety, description fully covers purpose, usage context, and parameter guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers the parameter with description (100% coverage). The description adds context that shortcode comes from URLs like /p/, /reel/, /tv/, enhancing understanding beyond schema.
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 it fetches raw Instagram post-page data by shortcode and lists specific metadata types (coauthors, tagged users, etc.), distinguishing it from sibling tools like get_instagram_posts.
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?
Explicitly says to use when fresh raw data is needed and not guaranteed on cached endpoints, providing clear usage context. Lacks explicit 'when not to use' but implies it effectively.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the tool is known to be safe. The description adds valuable behavioral details: defaults for sort and limit, cap at 50, pagination via cursor, and the return fields (caption, media URL, counts, timestamps plus has_more/next_cursor). No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: starts with a one-sentence summary, then details usage, parameter behavior, return data, and ends with two concrete examples. Each sentence adds value, and it is not overly long. Information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, sorting, pagination, output schema), the description covers all essential aspects: how to identify the creator, sorting options, pagination mechanics, return fields, and even example usage scenarios. The presence of an output schema reduces the need to detail return values, but the description still mentions key fields.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds meaning beyond the schema: it explains the mutual exclusivity of creator_id vs platform+username, states defaults and max for limit, describes the sort options with brief explanations, and clarifies the cursor’s source. This enhances the agent's understanding.
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 explicitly states 'Fetch a creator's posts, sorted and paginated' and provides concrete examples of user queries that trigger this tool. It distinguishes from sibling tools by clarifying the scope (a specific creator, with sorting/pagination) and mentions an alternative path (using after get_profile), making the purpose clear and distinct.
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?
The description includes explicit when-to-use scenarios like 'when the user asks to see what a creator has posted' and gives example queries. It explains the two identification methods (creator_id or platform+username) and mentions a workflow after get_profile. While it does not explicitly list when not to use, the examples and context provide strong guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. Description adds that it returns both profile and creator record, that case-insensitivity is handled server-side, and implicitly confirms read-only behavior. No contradictions.
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?
Well-structured with bolded purpose, bullet-point examples, and clear usage notes. Slightly verbose but front-loaded with the critical information, every sentence is relevant.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description effectively covers context: when to use, alternatives, parameter format, and error-prevention tips. No gaps for a simple 2-param tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema already covers 100% of parameters with descriptions. The description adds value by advising to omit the '@' sign and providing examples of how to parse platform and username from user input.
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 explicitly states 'Fetch a single social profile by (platform, username)' and lists the returned data (bio, metrics, growth, etc.), clearly distinguishing it from siblings like search_creators and get_creator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance: use this tool for exact handle+platform, avoid search_creators for exact lookups, and consider get_creator or lookup_profiles as alternatives. Includes concrete examples for different user inputs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only; description adds that it's a 'low-cost preview tool' and only returns one sample creator, providing behavioral context beyond annotations.
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?
Sentences are purposeful and front-loaded, though slightly verbose; each sentence contributes clear guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Fully covers purpose, usage limitations, behavioral expectations, and even includes a user-facing script; no gaps given annotations and output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist; baseline score for 0-param tools is 4, and description adds no param info, which 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?
Description clearly states it fetches a sample creator for preview before account linking, and explicitly distinguishes from siblings by forbidding search, discovery, matching, or lookalike uses.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (preview before linking) and when not (for search, discovery, etc.), and provides post-call instructions to explain account options.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations readOnlyHint=true and destructiveHint=false indicate safe read. The description adds beyond annotations by stating response splits into data and not_found, and that profiles are returned in no particular order, requiring re-correlation for order preservation. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with purpose, then usage guidelines, examples, and behavioral notes. Every sentence adds value, no fluff. Appropriate length for the complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (one complex array parameter), the description covers purpose, usage, response structure (data/not_found), and ordering behavior. It references output schema implicitly. No gaps for agent decision or invocation.
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% with descriptions for platform (enum) and username (string constraints). The description adds context about batch size limit (up to 100) but otherwise rephrases schema info. With high coverage, baseline 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 'Batch-fetch up to 100 profiles by (platform, username) pairs,' specifying the action, resource, and key parameters. It distinguishes from siblings like get_profile (single) and semantic_search_creators (fuzzy/topical) by emphasizing exact batch lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit when-to-use guidance is given: 'Use this when the user has a list of handles...' and 'One round-trip beats 30 calls to get_profile.' When-not-to-use scenarios and alternatives are named: get_profile for single exact, search_creators/autocomplete_creators for fuzzy, semantic_search_creators for topical. Examples further clarify.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds context about return values (match score, decision, structured reasons) and parameter usage. It does not contradict annotations and provides useful behavioral details beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose, usage guidelines, parameter details, sibling tool comparisons, and examples. Every sentence is necessary and front-loaded with the core purpose. No fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters, output schema exists, annotations present, siblings distinguished), the description covers what it does, how to call it, what it returns, when to use vs alternatives, and even includes a workflow example. It is fully complete for an AI agent to understand and use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining how to pass candidates (creator_ids and/or profiles), clarifying intent_query as 'the brief the LLM reasons against', and providing examples. This goes beyond the schema descriptions.
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 starts with a clear verb and resource ('Score how well specific creators fit a campaign brief or search intent'), and explicitly distinguishes itself from siblings like semantic_search_creators, search_creators, and find_lookalike_creators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool (when candidates are already in mind) and when not to use it (e.g., use semantic_search_creators for discovery, search_creators for resolving handles, find_lookalike_creators for similar creators). It also includes examples and a workflow.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. Description adds that it is 'cheap, fast' and explains legacy routing behavior without contradiction.
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?
Well-structured with front-loaded purpose, clear examples, and logical flow. Slightly long but justified given complexity. No wasted sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Fully covers usage, alternatives, legacy behavior, and parameter guidance. With 12 parameters, 100% schema coverage, and output schema present, the description is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds value by explaining how to use query_type (creator_lookup vs semantic_discovery) and providing usage context for backward-compatible parameters.
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?
Clearly states 'Find a creator by name/handle' and 'preserving legacy semantic creator search.' Distinguishes from siblings like get_profile and semantic_search_creators by specific use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use vs. when-not-to-use with concrete examples, including preferred alternatives (get_profile for exact handles, semantic_search_creators for niche discovery).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds that it uses hybrid vector search and returns a ranked list with specific fields, which is consistent and enhances transparency.
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 relatively long but well-structured with sections and examples. It is front-loaded with the purpose and every sentence adds unique value, though slight reduction could be possible.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 9 parameters fully covered by schema, annotations present, and output schema existing, the description still adds rich behavioral context, usage guidance, and examples, making it fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by clarifying the query parameter should not contain exact handles and explains how to use follower/engagement/verified params for constraints.
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 performs 'semantic discovery search for influencers/content creators using natural-language queries,' which is specific and distinguishes it from sibling tools like search_creators and get_profile.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use (e.g., topic, audience, geography) and when not to use (exact handles), provides alternatives like get_profile, search_creators, lookup_profiles, and includes concrete examples.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint and non-destructive. Description adds behavioral details: resolution through profile endpoint for platform+username, combined return, and include parameter effect. No contradictions.
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?
Well-structured with bullet points and examples, but slightly longer than minimal. However, every sentence adds value and it's front-loaded with purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given output schema exists (not shown but noted), description doesn't need return details. It covers input modes, resolution, alternatives, and handling of include. Complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% but description adds context on parameter usage, the two input modes, and the include parameter behavior. Examples clarify real-world usage.
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 the full record for a single creator by ID or exact platform+username. It distinguishes from siblings like search_creators, get_profile, and lookup_profiles via examples.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (have UUID or exact platform+username) and when not to use (batch lookups -> lookup_profiles; profile metrics -> get_profile). Provides clear alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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