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johnx438-hub

dsh-inbox-mcp

by johnx438-hub

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation5/5

    dsh_inbox_status reads/polls session state while dsh_inbox_deliver writes/sends a prompt; there is no overlap in their actions. An agent can easily choose the right tool based on whether it needs to observe or act.

    Naming Consistency4/5

    Both tools share the clear dsh_inbox_ prefix and use snake_case, so they are instantly recognizable as part of one server. The minor deviation is that one name uses a noun (status) and the other uses a verb (deliver), rather than a uniform verb_noun pattern.

    Tool Count3/5

    Two tools is at the low end of the acceptable range and feels thin for a general MCP surface. For the narrow status-and-deliver purpose the count is reasonable, but it is borderline rather than solidly well-scoped.

    Completeness4/5

    The core poll-and-deliver loop is covered: status tells whether the session is ready or busy, and deliver handles the different queueing modes. Mino gaps exist around inspecting queued messages or listing multiple sessions, but agents can generally work around these.

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

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

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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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

  • 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, and it does so reasonably well by naming the API method, the returned status fields, and the non-blank default selection behavior. It does not cover error behavior, authentication, or rate limits, but for a simple polling operation the disclosed behavior is sufficient for an agent to form accurate expectations.

    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 entire description is one efficient sentence that front-loads the action and resource, then supplies the key parameter behavior. Every phrase earns its place, and there is no redundant or filler content.

    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 a single optional parameter and no output schema, the description names the underlying endpoint, the fields returned, and the default selection rule, which is enough to invoke it correctly. It does not enumerate possible return shapes or error cases, but those are less critical for a simple status-polling tool.

    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 already documents the single parameter with 100% coverage and even says 'omit = latest non-blank.' The description repeats this nuance but adds no new format, constraints, or example beyond what the schema provides, so it meets the baseline for schema-heavy parameter documentation.

    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 ('Poll') and names the exact resource ('DSH session status') and underlying method ('session.list'), plus the fields it returns (running, title, updatedAt). This makes its purpose unmistakable and distinguishes it from the sibling dsh_inbox_deliver, which clearly handles delivery rather than status.

    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 gives clear operational guidance: omit session_id to target the most recently updated non-blank session, which tells an agent exactly when the optional parameter should be left out. It does not explicitly state 'use this instead of dsh_inbox_deliver,' but the contrasting verb/resource makes the usage context clear enough without an explicit exclusion.

    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 full burden of behavioral disclosure. It explains trust/auth requirements, the need for from_id attribution, blocking of dangerous shell/exfil patterns, and the local service dependency. It does not describe return values or error behavior, but it provides substantial transparency 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.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is compact and information-dense, with the core action front-loaded and supporting details (mode semantics, auth, safety, local requirement) following. Each sentence contributes useful information. Some acronyms and DSH-specific terms are used without expansion, which slightly reduces accessibility.

    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 6-parameter tool with no annotations and no output schema, the description covers the key operational context: delivery modes, trust pairing, attribution, safety blocking, local endpoint, and session targeting. It lacks an example body and does not tell the agent how to confirm delivery via the sibling status tool, but the core calling context is present.

    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 the baseline is 3. The description adds meaningful semantics beyond the schema: it explains how kind affects delivery routing, why trust_id/house_id matter, why from_id should be passed, and the fallback behavior of session_id. This gives an agent practical guidance for choosing and filling 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 states a specific action with a concrete target: 'Deliver a message into a DeepSeek Harness (DSH) Web session via session.prompt.' It also explains the meaning of the three delivery modes, so an agent can understand what the tool does without opening the schema. This clearly distinguishes it from the sibling dsh_inbox_status, which presumably reports status rather than delivering messages.

    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 gives clear mode-selection context: kind=auto routes based on busy/idle state, steer forces mid-turn inject, and task always queues. It also lists prerequisites such as matching house_id/trust_id when DSH_INBOX_TRUST is set and the need for a local dsh web instance. However, it does not explicitly state when to prefer dsh_inbox_status or mention alternatives/exclusions.

    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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  • Evaluate tool definition quality.

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