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davidmosiah

TikTok Agent Publisher

Server Quality Checklist

83%
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  • Latest release: v0.1.5

  • Disambiguation5/5

    Each tool serves a clear, distinct function: manifest provides metadata, connection_status checks readiness, list_videos retrieves videos, privacy_audit examines safety, publish_status queries job state, publish_video creates a publish job. No overlap.

    Naming Consistency5/5

    All tool names follow the consistent pattern 'tiktok_verb_noun' in snake_case, making it easy for an agent to predict tool names and purposes.

    Tool Count5/5

    With 6 tools, the set is well-scoped for a TikTok publishing server, covering essential operations without unnecessary bloat.

    Completeness4/5

    The set covers the main publishing lifecycle: list, publish, status, and safety checks. Minor gaps exist (e.g., no tool for updating or deleting a video), but these are outside the core publishing focus.

  • Average 3.1/5 across 6 of 6 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 9 commits in the last 12 weeks
    • Last stable release on
    • 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.

  • This server has been verified by its author.

  • Add related servers to improve discoverability.

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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

  • Behavior3/5

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

    Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds 'safety guidance' context but doesn't detail behavioral traits like what the manifest contains or how it affects agent behavior.

    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 single short sentence, concise and front-loaded. It conveys the core purpose efficiently without unnecessary words.

    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?

    The description lacks details on the return value format or usage context. Given the absence of an output schema, the agent needs more information to interpret the manifest output correctly.

    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 0% and the description does not explain the 'client' or 'response_format' parameters. Although the parameter names are somewhat self-explanatory, the description should add meaning, which it fails to do.

    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 specifies the tool returns 'machine-readable install, client, runtime and safety guidance for agents.' While it doesn't use a verb+resource pattern, it clearly distinguishes this manifest tool from sibling tools that handle videos or connection status.

    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 explicit guidance on when to use this tool versus alternatives. The description implies it's for agents needing guidance, but doesn't provide criteria or exclusions.

    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 confirms it is a read-only operation (returns data), consistent with annotations (readOnlyHint=true, destructiveHint=false). It does not contradict annotations. However, it adds no extra behavioral context beyond what annotations already provide, such as rate limits or whether the audit is cached.

    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 single sentence (15 words) with no redundancy. It is concise, but the phrasing is somewhat cryptic ('safety boundaries') which slightly reduces clarity. Still, it front-loads the key action and resource.

    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?

    No output schema is present, so the description should explain what the returned 'safety boundaries' contain. It does not detail the structure or fields of the result. For a privacy audit tool, users need to know what kind of data (e.g., warnings, compliance status) they will receive. The description leaves this vague.

    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 0% and the only parameter, 'response_format', is not explained in the description. The schema shows it's an optional enum with defaults, but the description does not clarify that this parameter controls output format (JSON vs markdown). Given the low coverage, the description should compensate.

    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 clearly states the tool returns 'safety boundaries' for various aspects (token, media-hosting, local-file, live-publish), which aligns with the title 'TikTok Privacy Audit'. It distinguishes this tool from siblings like tiktok_list_videos or tiktok_publish_video by focusing on privacy audit results. However, 'safety boundaries' is somewhat jargon and could be more explicit.

    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 on when to use this tool vs alternatives. The description does not mention prerequisites, contexts, or when not to use it. With siblings like tiktok_connection_status, a user might need clarification on when to audit privacy versus check connectivity.

    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?

    Annotations already provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds that the videos are 'recent' and visible to the token, but does not disclose pagination behavior, rate limits, or what 'recent' means. Adequate but not rich.

    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 single concise sentence that efficiently communicates the purpose. It is not verbose, though it could be slightly expanded without losing conciseness.

    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?

    Given no output schema and undocumented parameters, the description is insufficient. It does not explain the response format, pagination, or what constitutes 'recent'. More detail is needed for a complete understanding.

    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?

    Schema description coverage is 0%, and the description does not mention any parameters. The three parameters (cursor, max_count, response_format) are left unexplained, leaving the agent without guidance on their 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 action 'list', the resource 'TikTok videos', and the scope 'visible to the configured OAuth token'. This distinguishes it from siblings like tiktok_publish_video and tiktok_privacy_audit.

    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?

    The description does not provide explicit guidance on when to use this tool vs alternatives. No comparison with sibling tools like tiktok_agent_manifest or tiktok_connection_status is given. Usage context is implied but not clear.

    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, destructiveHint false, and idempotentHint true, so the tool's safety is clear. The description adds value by explicitly noting that tokens are not exposed, which is a key behavioral trait 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?

    The description is a single, focused sentence that front-loads the tool's purpose. It is concise without wasted words, though it could benefit from including parameter guidance.

    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 optional parameter and no output schema, the description should explain what the output looks like or what the checked states mean. It mentions readiness checks but gives no return format details, leaving the agent uninformed about expected results.

    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?

    Schema description coverage is 0%, meaning no property descriptions in the schema. The tool's description provides no additional meaning for the lone parameter (response_format), leaving its purpose entirely to the schema which lacks narrative context.

    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 checks dry-run mode, OAuth readiness, and live publish readiness, using the verb 'check' with specific aspects. It distinguishes itself from siblings like tiktok_publish_status by focusing on connection state rather than publishing status.

    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 explicit guidance on when to use this tool versus alternatives. While sibling tools are listed, the description does not contrast usage contexts or provide when-to-use/when-not-to-use advice.

    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?

    Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, fully covering safety and idempotency. The description adds no extra behavioral context (e.g., rate limits, auth, or response structure), so it meets baseline but adds little value.

    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?

    Single sentence with 9 words, front-loaded with verb and resource. No redundancy; every word serves a purpose.

    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?

    Despite good annotations, the description lacks parameter details and does not explain the output format or how the status relates to other tools. Agents may not know what response_format values do or what to expect in the response.

    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 coverage is 0%, but the description only mentions 'publish id' without explaining the parameter name or meaning of 'response_format'. It fails to compensate for missing schema descriptions, leaving agents uncertain about optional 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?

    Description clearly states the action (Fetch), resource (publish status), and required input (publish id). It distinguishes from sibling tools like tiktok_publish_video (which creates) and tiktok_privacy_audit (different resource).

    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 explicit guidance on when to use this tool versus alternatives. Only implied that it should be used when a publish id is available and status is needed, but no exclusions or context for sibling tools.

    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?

    Annotations already indicate non-read-only (readOnlyHint=false) and non-destructive (destructiveHint=false). Description adds the dry-run behavior, which is useful context. But it does not disclose other behavioral traits like response format, error handling, or side effects beyond job creation.

    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 short sentences, each adding value: first states purpose, second gives critical behavioral note. No filler or redundant information.

    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?

    Despite the complexity of 6 parameters and no output schema, the description is minimal. It fails to explain parameter usage, return values, or workflow details (e.g., what happens after job creation). The agent needs more context for proper use.

    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?

    Schema description coverage is 0%, yet the description adds no information about the 6 parameters (video_path, title, caption, etc.). The agent is left with only parameter names, enums, and types, which is insufficient for correct invocation.

    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 'Create a TikTok video publish job,' using a specific verb and resource. It is distinct from sibling tools like tiktok_list_videos and tiktok_publish_status, which focus on listing or status checking.

    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?

    Description provides clear guidance on dry-run default and environment variable for live mode. However, it lacks explicit when-not-to-use instructions or prerequisites (e.g., requiring authentication or video file format).

    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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