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by indianic

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: v1.6.1
Disambiguation5/5
Each tool targets a distinct resource and action. Even the list_* tools (sites, authors, personas) are clearly separated by what they enumerate, and the descriptions clarify the differences. No two tools could be easily confused.
Naming Consistency4/5
The vast majority of tools follow a consistent verb_noun pattern (list_sites, add_site, create_post, update_post). The only deviation is health_check, which is a common compound noun and not confusing, but it breaks the otherwise uniform verb-first style.
Tool Count5/5
14 tools is within the ideal 3-15 range. Each tool serves a clear purpose in the blogging workflow, from configuration and research to image generation and publishing. No tool feels redundant or unnecessary.
Completeness3/5
The set covers site management, persona lookup, research, brief building, scoring, image handling, and post creation/updating, but lacks any way to read or delete posts. This is a notable gap for a publishing server, as an agent cannot list existing posts or retrieve a post to update it intelligently.
Average 4.1/5 across 14 of 14 tools scored. Lowest: 2.6/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 59 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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.
Add a glama.json file to provide metadata about your server.
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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a read-only operation but does not state this explicitly, nor does it mention error handling, permission requirements, or what happens when the slug is invalid. Minimal behavioral context is added.
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 extremely short and front-loaded, using a dash to present key attributes. It is efficient and avoids waste, though it is a fragment rather than a complete sentence. Every word contributes meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one parameter and no output schema or annotations, the description is insufficiently complete. It specifies the general content of the profile but omits the meaning of the input, return format, and any edge-case behavior. An agent would need to guess at slug semantics and result structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, and the tool description does not mention the 'slug' parameter at all. The agent is left without any explanation of what a slug is or how to supply it, so the description fails to compensate for the missing schema information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Full author profile — voice, style, bias, and instructions' clearly identifies the tool's output as a comprehensive persona profile, differentiating it from the sibling list_personas tool. Though no explicit verb is present, the resource and scope are specific enough for an agent to infer the retrieval intent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as list_personas or other author-related tools. The description gives no context about prerequisites, use cases, or situations where a different tool would be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description takes on the burden of disclosure. It reveals that secret credential fields are stored as .env variable references rather than literal values, which is important behavioral context. However, it does not mention other traits such as overwrite behavior, validation, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact, with the main purpose stated in the first sentence and a security-relevant caveat in the second. While the caveat repeats schema content, it's relevant and doesn't bloat the description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple add operation, the description covers the core purpose and secret handling, but lacks specifics on outcomes, error scenarios, or integration with other site-management tools. The presence of nested objects and no output schema suggests more detail could be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not add meaning beyond the schema; the secret-field behavior it mentions is already stated in the credentials parameter description. It also does not clarify the url or default_author parameters, leaving 40% of the schema without additional 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 tool's function with a specific verb and resource ('Add a publishing target to config/sites.yaml'). This distinguishes it from sibling tools like remove_site and list_sites.
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 implies usage (adding a publishing target) but does not explicitly provide when-to-use guidance or contrast with alternatives. The secret-handling caveat offers a directive but not usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It names the action and return value (hosted URL) but does not disclose side effects, error behavior, or prerequisites. The transparency is adequate but minimal.
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 a single, clear sentence with no redundant or extraneous information. It is appropriately sized for the tool's simplicity.
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?
For a simple tool with three parameters and no output schema, the description conveys the core functionality and return value. It could mention prerequisites like 'site must be existing' but is otherwise sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 33% (only 'path' is described). The description does not add meaning for 'site' or 'alt', leaving their roles ambiguous.
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 action (upload), the object (local image), the destination (site's media store), and the result (hosted URL). This distinguishes it from sibling tools like generate_image which creates an image.
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 implies usage: when you have a local image to host, upload it to a site. However, it does not explicitly mention alternatives, exclusions, or prerequisites such as the site needing to exist.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 clearly indicates a read-only listing operation, which is inherently transparent. However, it does not disclose any additional behavioral traits such as ordering, filtering, or whether the list includes inactive or draft personas, which could be relevant for an agent.
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 a single, concise sentence that is front-loaded with the action and object. Every word earns its place; there is no fluff or redundancy. It is optimally sized for the simplicity of the tool.
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 tool's low complexity (no parameters, no output schema, simple list operation), the description is nearly complete. It could be slightly more informative by noting that the list is of pre-defined/available author personas, but the current level is sufficient for an agent to understand the tool's basic purpose.
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?
The input schema has zero parameters, so the baseline is 4. The description adds no parameter information because there are none to describe. This is appropriate and requires no further elaboration.
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 uses a specific verb 'List' and clearly identifies the resource as 'available author personas.' This distinguishes it from sibling tools like list_authors (which likely lists authors) and get_persona (which fetches a specific persona), 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 Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool versus alternatives. While it is implied that this is for seeing available author personas, the description does not mention when not to use it or how it differs from list_authors or get_persona. The agent receives no directional context beyond the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. The statement 'Leaves .env untouched' provides useful scope, but it does not disclose other behaviors such as reversibility, error handling, or whether the operation is permanent. This is a moderate level of transparency.
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 two concise sentences, front-loaded with the core action and followed by a useful caveat. Every word earns its place, with no redundancy or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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, so the description is mostly adequate. It states the action and scope, but it fails to mention return values, error cases, or what happens if the slug doesn't exist. For a clean removal tool, it is acceptable but lacks some contextual completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one required parameter 'slug' with no description, and the tool description does not explain what slug refers to. Given 0% schema description coverage, the description should have clarified that slug is the identifier of the site to remove, but it does not, leaving the agent to infer meaning.
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 uses a specific verb 'Remove' and a clear resource 'publishing target from config/sites.yaml', which precisely defines the action. It also distinguishes itself from sibling tools like add_site and list_sites by focusing on the removal operation.
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 implies when to use it by specifying the action and the target file (config/sites.yaml), giving clear context. However, it does not explicitly state when not to use it or list alternatives, so it doesn't fully meet the highest standard.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the key behavioral trait that only passed fields are changed, which is valuable for a partial-update tool. It also mentions the scheduling/unscheduling/backdating behaviors. However, with no annotations, it omits details about permissions, error conditions, or whether changes are irreversible, leaving the agent to infer mutation safety.
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 three short, purposeful sentences. The first states the core action, the second explains the partial-update behavior, and the third lists additional use cases. Every sentence earns its place with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description gives enough context to understand primary use and the scheduling nuances. But with 22 parameters, no output schema, and no annotations, it leaves out return values, error handling, and permission requirements. It is adequate for basic usage but not fully complete for an agent operating autonomously.
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 description adds semantics for status and publish_at by explaining their combined usage for scheduling/unscheduling/backdating, and it clarifies that any subset of fields can be updated. Schema coverage is only 9%, so the description should compensate for the other 20 parameters; it does not, though most property names (e.g., title, tags, html) are self-explanatory.
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 opens with 'Edit an existing post in place,' which clearly states the verb (edit), resource (existing post), and scope (in place). It further distinguishes itself from the sibling create_post by emphasizing edits to existing posts and by enumerating specific use cases like scheduling/unscheduling drafts and backdating.
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 explicitly lists when to use the tool: to edit a post, schedule an existing draft, unschedule one, or correct a date. It implicitly signals this is not for creating new posts, but it does not explicitly name create_post as an alternative or state what not to do. Clear context exists, but no formal exclusions are given.
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?
No annotations are provided, so the description carries the full burden. It discloses the output format (platform ids) and adds behavioral context by explaining how the ids can be used in create_post and persona configuration, which goes beyond a simple listing statement.
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 and well-structured: the first sentence states the purpose, and the second provides usage guidance. No unnecessary words or fluff.
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 tool's simplicity (one parameter, no output schema, no annotations), the description covers the core behavior, output, and intended usage. It lacks parameter details but is otherwise complete for a listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides 0% description coverage for the sole 'site' parameter, and the description only mentions 'on a site' without explaining what a valid site is (e.g., site id or name) or how to obtain it. The description does not compensate for the lack of schema information.
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 'List the author accounts on a site, with their platform ids,' specifying the verb, resource, scope, and output. It also distinguishes authors from personas, which is helpful given the sibling tool list_personas.
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 provides concrete usage guidance: 'Pass an id as create_post's author to byline someone who has no persona file, or copy it into a persona's platform_authors.' This explains when to use the tool but does not explicitly mention when not to use it or name alternatives like list_personas.
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?
With no annotations, the description carries the full burden. It discloses key behaviors: provider fallback (Gemini then Grok), file output (writes a PNG under the runs directory), and return value (path plus provider). It doesn't cover failure modes or auth/rate limits, but for this tool the disclosed behavior is substantial and directly actionable.
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 compact—three sentences—and front-loads the primary action and fallback. Every sentence provides essential information (what, how to phrase prompt, output behavior). No redundant wording or fluff.
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?
For a tool with 6 parameters, 1 required, and no output schema, the description covers the essential context: purpose, fallback, output location, and return content. It doesn't describe the full parameter matrix, but the schema handles that. The description sufficiently orients the agent without needing to repeat schema details.
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 high (83%), so the schema already explains most parameters. The description adds minimal parameter context—chiefly emphasizing that the prompt should be subject-only and that style is applied automatically. This aligns with existing schema descriptions, so the description adds limited extra meaning beyond the 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 a specific action: 'Generate a photograph with Gemini, falling back to Grok.' It identifies the resource (a photograph/PNG) and outcome (writes a PNG, returns path and provider). This distinguishes it from siblings like upload_image, which handle existing images rather than generating new ones.
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 provides explicit guidance on how to use the tool: 'Pass `prompt` as the SUBJECT ONLY' and explains that style is applied automatically. It doesn't explicitly contrast with alternatives (e.g., when to use upload_image instead), but the generation context is clear, making the usage circumstances easy to infer.
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?
With no annotations, the description carries full behavioral burden. It discloses default status, author resolution, the [[content_image]] placeholder constraint, and image requirement/refusal behavior. While it doesn't cover every edge case, it addresses the most consequential behaviors.
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?
Four sentences, each providing necessary operational detail. It front-loads the core action and then layers critical caveats without redundancy or fluff.
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?
For a 25-param create tool with no output schema, the description covers the main behavioral complexity (status, images, author) while the schema's rich parameter descriptions handle the rest. It lacks explicit return-value info, but the schema and sibling context partially compensate.
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 60%, and the description adds practical semantics for key parameters: status defaults, author resolution, and image options with default behavior. It compensates for gaps but doesn't fully explain all 25 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?
States 'Publish an article' with a specific verb and resource, and clarifies default status (published) and creation semantics. Clearly distinguishes from siblings like update_post and upload_image by framing it as the create/publish action.
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?
Provides clear context on when to use 'draft', 'scheduled', or 'published' statuses, and explains author field resolution. Does not explicitly name alternatives like update_post for existing posts, so it lacks explicit 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It clearly states the tool is mechanical, makes no external API calls, and explains the conditional nature of the citation provenance and feature-image checks. It does not describe the full output structure, but 'Verdict blocked' hints at the verdict format.
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 three sentences with no filler. It front-loads the core purpose and enumerates checks efficiently, then adds conditional behavior in a compact em-dash clause. Every sentence earns its place.
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 has no output schema and multiple nested optional parameters, but the description covers the key behavioral aspects: what is scored, when verdicts matter, and what happens when optional inputs are omitted. It lacks explicit thresholds and return-format details, but the guidance is sufficient for an agent to select and invoke 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 description coverage is 75%, so the schema already documents most parameters. The description adds meaningful context for the two optional parameters: findings enables the citation_provenance check, and feature_image is invisible to the tool unless supplied. This goes beyond the schema's field-level descriptions and helps the agent decide whether to pass them.
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 opens with a specific verb+resource ('Mechanically score a draft') and enumerates the exact scoring dimensions (burstiness, AI-tell phrasing, paragraph uniformity, etc.), making the tool's purpose unmistakable and clearly distinguishing it from sibling tools like create_post or health_check.
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 implies usage context: it is meant for evaluating a draft before publishing, as shown by 'Verdict blocked means fix before publishing.' It also clarifies optional behavior with findings and feature_image. However, it does not explicitly state when not to use this tool or name alternative tools for related tasks.
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?
With no annotations provided, the description carries full responsibility for behavioral disclosure. It explicitly states a key safety guarantee ('Never returns key material') and implies a read-only nature via 'List'. This goes beyond the minimum, though it does not cover authentication or error scenarios.
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 two short sentences, front-loaded with the action and resource. Every word adds value: 'configured' clarifies scope and 'Never returns key material' is a critical guarantee. No redundancy.
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?
For a simple zero-parameter list tool, this description is fully complete. It states what it returns (configured publishing targets) and an important exclusion (key material). No output schema exists, but the description covers the essential return value sufficiently.
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?
The tool has zero parameters, so the description does not need to explain any. The baseline score of 4 applies because there is nothing missing regarding 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?
The description uses a specific verb ('List') and resource ('configured publishing targets'), clearly distinguishing it from sibling tools like add_site and remove_site. The scope is well-defined and immediately understandable.
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 clearly communicates that this tool is for listing configured publishing targets, which is contextually distinct from the add/remove siblings. It does not explicitly exclude any use cases or name alternatives, but the purpose itself is sufficient for an agent to decide when to invoke it.
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?
With no annotations, the description carries the full burden and it delivers: it discloses refusal behavior, verification criteria, warning marking for out-of-window findings, trust levels for the research origin, and return fields (seed, researchOrigin, warnings). This goes well beyond what the schema provides.
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 a dense single paragraph, but most sentences carry operational rules (refusal, verification, asking the user). It is front-loaded with purpose and avoids filler, though the all-caps emphasis and some repetition of schema text slightly reduce elegance.
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?
For a 9-parameter tool with a nested object and no output schema, the description addresses the main ambiguity (research origins) and tells the agent what to return (seed, researchOrigin, warnings). It doesn't describe the brief's output format or side effects, but these are less critical than research handling. It is largely complete for safe invocation.
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 only 33%, so the description must add meaning. It does for the critical parameters research/findings/mode, explaining mutual exclusivity, mandatory news-mode research, and how to choose them, but persona, word_count, language, and seed are left self-evident. Overall it compensates for the low coverage on the high-stakes 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?
The opening sentence uses the specific verb 'Build' with a concrete deliverable ('randomized, persona-specific writing brief') and scope ('voice, structure, visual blocks, AEO and GEO'). This clearly differentiates it from siblings like research_topic (research only) and create_post (publishing).
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?
It explicitly states RESEARCH IS MANDATORY IN NEWS MODE, gives exactly one origin, and says passing both is refused. It also directs the agent to ASK THE USER when unclear and to use blog mode for evergreen topics, providing clear when-to-use and 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.
Behavior4/5
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 discloses the scope (all blogs, image/research providers), granularity (per-API), and result semantics (ok/fail with real error). It does not mention potential side effects or performance implications, but as a health check the behavioral profile is well covered.
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 deliver the purpose, scope, output, and usage directive with no redundancy. The description is front-loaded with the action and immediately provides actionable 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?
For a parameterless diagnostic tool with no output schema, the description fully covers what it does, what it affects, what it returns, and when to use it. It is complete for its simplicity.
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?
The tool has zero parameters and schema coverage is trivially 100%, so the description need not add parameter details. The baseline score for 0-parameter tools is 4, and the description appropriately focuses on behavior rather than 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?
Clear verb 'probe' plus specific resources: every configured blog, image provider, and research provider. The output format (per-API ok/fail with error) is also stated, fully distinguishing this from all sibling tools.
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 instructs 'Run this first when anything fails', giving a clear when-to-use directive. While no alternatives are mentioned, none are needed since this is the designated diagnostic tool.
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?
With no annotations, the description carries the full transparency burden and does so comprehensively. It discloses provider refusal (never swaps), absence of re-sorting or relevance filtering, provenance formatting, the advisory (non-blocking) nature of downstream checks, and the distinction between verified findings and untrusted hand-supplied strings. This goes far beyond the schema.
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?
Though long, every sentence earns its place. The description is logically structured: purpose, alternatives, provenance value, downstream use, recency decision, provider policy, output handling, and explicit do-not-summarize warning. It front-loads the core action and builds context without 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?
This is a complex tool with no output schema and no annotations. The description fills every gap: what it returns (findings with URLs and dates), order, provider behavior, configuration, downstream integration, and failure modes (refused unconfigured provider). An agent has enough context to invoke it correctly and interpret results.
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 75%, so the baseline is 3. The description adds significant value by detailing provider-specific behavior ('Brave returns ranked snippets with no synthesis; Tavily also returns a synthesis (`answer`) plus its own sources') and reinforcing window semantics ('Use "day" for something that happened in the last few hours'). max_results lacks schema description but its schema bounds (1-20, default 10) provide adequate meaning; the description does not add further detail there, so not a 5.
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 opens with a specific verb and resource: 'fetch attributable findings on a topic from a single configured research provider.' It clearly distinguishes itself from sibling tools like build_writing_brief and score_draft by emphasizing provenance and downstream checks, making its unique role unmistakable.
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 on when to use this tool versus alternatives: 'If you already have live web access, use it directly and pass what you find as `research` to build_writing_brief instead.' It also instructs when to ask the user if recency is unclear, and explicitly warns against summarizing findings into `research`, naming the alternative approach clearly.
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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