跳过已自行完成的安排步骤
skip_dispatch_step【需要登录】用户明确表示这步自行搞定/不再需要时跳过,终结该步骤未接受建议并推进后续步骤,可能触发平台 LLM 排人。结果不明或超时后先查询现值,不要自动重发;服务没有持久请求去重键。 用 get_my_dispatch 核对。
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| stepId | Yes |
skip_dispatch_step【需要登录】用户明确表示这步自行搞定/不再需要时跳过,终结该步骤未接受建议并推进后续步骤,可能触发平台 LLM 排人。结果不明或超时后先查询现值,不要自动重发;服务没有持久请求去重键。 用 get_my_dispatch 核对。
| Name | Required | Description | Default |
|---|---|---|---|
| stepId | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds valuable behavioral context beyond the annotations: login is required, skipping may trigger platform LLM staffing, and there is no persistent deduplication key. It explains the destructive nature by saying the step's unaccepted suggestion is terminated and later steps are advanced, consistent with destructiveHint=true and idempotentHint=false.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three dense sentences carry all essential information: trigger condition, effect, side effect, retry guidance, and verification path. The content is front-loaded with the login requirement and usage condition, with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a single parameter, no output schema, and a destructive mutation, the description covers the important operational concerns: when to act, what changes, what may be triggered, how to handle ambiguity, and how to verify. Enough is provided for an agent to call the tool safely.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter, stepId, is not described at all in the description, and schema description coverage is 0%. The phrase 'this step' is too generic to explain where stepId comes from, what identifiers are valid, or how it maps to a dispatch step.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb and resource: skip a dispatch step when the user explicitly says they will handle it themselves or no longer need it. It also explains the effect: ending the unaccepted suggestion and advancing subsequent steps, which distinguishes it from accept/decline dispatch actions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives an explicit when-to-use condition: only when the user clearly indicates they will handle the step themselves or no longer need it. It also provides cautionary guidance: after an unclear result or timeout, query current state first, do not auto-retry, and use get_my_dispatch to verify.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly documented purpose, often with explicit 'when to use' guidance and cross-references, making the vast majority easy to tell apart. A few clusters (get_my_brief, get_my_positioning, get_my_work, get_my_dispatch) and data-overlapping get_my_card vs get_my_profile require careful reading, but descriptions are detailed enough to prevent serious misselection.
The overwhelming majority follow snake_case verb_noun conventions (create_product, update_need, list_my_signups). Minor deviations include noun-only feed names (personalized_feed, random_feed), inconsistency between 'prefs' and 'preferences' in notification tools, and a mix of update_* and set_* for mutations, but the pattern remains predictable overall.
137 tools is an extreme mismatch for any MCP server, far exceeding the 50+ threshold for a score of 1. Even with a broad multi-domain platform, this volume makes tool selection and navigation impractical and heavily burdens the agent's context window.
The surface covers full lifecycles for needs, products, activities/signups, conversations, collaboration goals/tasks, dispatch, profile/onboarding, and supporting resources like companies, parks, policies, and ratings. Deliberate omissions (no user-post creation, no organizer profile editing via agent) are explicitly documented, so core workflows have no obvious dead ends.