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hello-emrah

Svetovid

by hello-emrah
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools serve clearly distinct purposes: one provides project and timeline metadata, the other exports a frame as an image. There is no overlap or ambiguity.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun snake_case pattern: get_state and render_current_frame. Naming is uniform and predictable.

    Tool Count2/5

    With only 2 tools for a complex domain like DaVinci Resolve, the server feels significantly underdeveloped. While it covers basic inspection and frame export, many essential operations (e.g., editing, timeline manipulation) are missing.

    Completeness2/5

    The server provides only state retrieval and frame rendering, lacking any editing or modification capabilities. For a tool claiming to 'orient' and 'see the edit,' the absence of editing tools makes it incomplete for interactive workflows.

  • Average 4.3/5 across 2 of 2 tools scored.

    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
    • 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.

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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?

    No annotations are provided, so the description carries full behavioral burden. It discloses that the tool exports an image and requires specific conditions, but does not mention potential delays, error handling (e.g., if no frame), output format details, or side effects. Adequate but could be more transparent.

    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?

    Three concise sentences with no wasted words. The main action ('Export the frame...') is front-loaded, and the rest provides context. Every sentence serves a purpose.

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

    Completeness4/5

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

    Given no output schema, the description covers the essentials: what it does, when to use, and prerequisites. It lacks explicit mention of return format or error states, but for a simple tool with no parameters, it is largely complete.

    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 input schema has no parameters and schema description coverage is 100% (trivially). Per the rule, baseline is 3. The description adds no parameter information because there are no parameters, so score 3.

    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 exports the current frame as an image, using a specific verb ('Export') and resource ('frame at the playhead'). It also distinguishes itself from the sibling 'get_state' by emphasizing visual evidence over metadata.

    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 ('to look at what the timeline actually shows before and after an edit, rather than reasoning from metadata alone') and provides a prerequisite ('timeline must be open and a frame visible'). This effectively guides the agent on when to invoke this tool vs. 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?

    No annotations exist, so the description bears full burden. It discloses the tool reads state and returns detailed information (product, version, project, timelines, current timeline metrics). Missing minor details like prerequisites (e.g., open project) or error conditions, but overall good 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 extremely concise with two sentences that front-load the key instruction 'Call this first' and list return data efficiently. 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?

    Given the tool's simplicity (no parameters, no output schema), the description adequately covers its core function of returning state. It could mention potential failure cases (e.g., no open project), but overall is sufficiently complete for an agent.

    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 are defined, so the description adds no parameter detail. Baseline score of 4 is appropriate since schema coverage is 100% and no parameters exist.

    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 purpose: to orient in DaVinci Resolve and return state information. It uses specific verbiage like 'Call this first' and lists actionable return data, distinguishing it from the sibling tool 'render_current_frame'.

    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 advises 'Call this first,' providing clear guidance on when to use the tool. While it doesn't explicitly state when not to use it or discuss alternatives, the context of a single sibling tool makes the usage clear.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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