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krasnoff

sign-in-form

by krasnoff
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Hybrid

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only a single tool, there is no possibility of confusing it with another tool. The purpose of open-sign-in is clearly stated and unambiguous.

    Naming Consistency5/5

    The tool name follows a clear verb_noun pattern (open-sign-in) and there are no other tools to create inconsistencies. As the sole tool, it presents no naming conflicts.

    Tool Count3/5

    The server is reduced to a single tool, which feels thin even for a narrow purpose. While the scope is minimal, a complete sign-in flow would typically require additional tools such as submit_sign_in or validate_credentials, so the count is borderline.

    Completeness3/5

    The tool displays a sign-in form but offers no way to submit or process the entered credentials, leaving the agent unable to complete a sign-in action. This is a notable gap in the tool surface for a server that claims to handle sign-ins.

  • Average 3.8/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 4 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

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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 the burden of disclosing behavior. It does clarify that the tool displays an interactive form rather than performing authentication, which is useful. However, it does not disclose side effects, what happens after display, or whether any state changes occur.

    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 one short, front-loaded sentence with no filler. Every word adds meaning, and the sentence structure is immediately scannable for an agent.

    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, parameterless display tool, the description is mostly complete: it names the action and UI element shown. An output schema exists, so return-value details are presumably covered there. The main omission is usage context, but that is already reflected in the usage-guidelines score.

    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 an empty input schema, so there is no parameter semantics burden. The baseline for 0-parameter tools is 4, and the description reasonably does not need to document inputs.

    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 states a specific verb, 'Display', and a specific resource, 'an interactive username and password form'. This both matches the tool name and disambiguates it from a sign-in/authentication action. There are no sibling tools, so no differentiation is needed.

    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 gives no guidance on when to call this tool or when to avoid it. It only says what the tool does; there is no mention of prerequisites, context, or alternatives. With no siblings, some usage context would still help the agent decide when displaying a sign-in form is appropriate.

    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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