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dashboard_snapshot

Read-onlyIdempotent

One-call project snapshot: task counts, in-progress task titles, active release with progress, blocked count, pending feedback. The right first read for a session.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "projectId": "<projectId>",
      "context": "<context>"
    },
    "name": "dashboard_snapshot"
  }
}

Input Schema

NameRequiredDescriptionDefault
contextYesExplain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization."
projectIdYesThe project ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds value beyond that by disclosing the returned content set, which matters because there is no output schema. It does not mention whether in-progress task titles or feedback entries are truncated/limited, which is the main residual gap.

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 sentences, zero filler. The payload inventory is front-loaded and the usage cue follows it, so an agent learns what it gets before why to call it.

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 two-parameter read-only aggregate with no output schema, the description covers what matters: the categories returned and the intended call position in a session. It could note limits on list sizes (how many in-progress titles or feedback items come back), but nothing essential for correct invocation is missing.

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?

Schema description coverage is 100%; both parameters (projectId and the heavily-documented context param) are fully described in the schema itself. The description adds no additional meaning about parameter behavior, so the baseline 3 applies.

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?

States a specific verb and resource ("One-call project snapshot") and then enumerates exactly what it aggregates: task counts, in-progress task titles, active release with progress, blocked count, pending feedback. That inventory clearly separates it from single-purpose siblings like get_project, list_tasks, tasks_list_blocked, release_read_active, and feedback_hub_get.

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 right first read for a session" gives a clear situational trigger and implicitly steers the agent away from making several narrower reads first. It stops short of explicit exclusions — it never says when to prefer get_project or the individual list tools instead (e.g., when only one data category is needed).

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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