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This was a duplicate manual listing. Use Summer’s official listing, imported from the official MCP Registry. Summer’s MCP server remains active at https://api.gosummer.ai/mcp. Setup and documentation: https://gosummer.ai/docs/mcp-clients.

List published plans, newest first: who approved each (a person or an agent), whether it ran and was checked, the agent's self-review, its own call on running the plan without approval, and auto_run: what the channel's auto-run setting did or would do with it (outcome ran/would_run/would_wait, the deciding reason, channel, on/off, confidence bar and any saved auto-run decision), and runs_as: code when approved work runs, or ran, without an agent (a plan that only resolves the case, or sends one reply and then resolves it), otherwise agent

summer_plans_list
Read-onlyIdempotent

List published plans, newest first: who approved each (a person or an agent), whether it ran and was checked, the agent's self-review, its own call on running the plan without approval, and auto_run: what the channel's auto-run setting did or would do with it (outcome ran/would_run/would_wait, the deciding reason, channel, on/off, confidence bar and any saved auto-run decision), and runs_as: code when approved work runs, or ran, without an agent (a plan that only resolves the case, or sends one reply and then resolves it), otherwise agent. Includes totals comparing the agent's calls with people's decisions. Read-only.

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": {
      "company": "<company>",
      "environment": "<environment>"
    },
    "name": "summer_plans_list"
  }
}

Input Schema

NameRequiredDescriptionDefault
callNoThe agent's own call on running the plan without approval, judged against the company's autonomy rubric
showNoexecuted (default): plans whose approved work was sent to run; all: every published plan
cursorNo
companyYesSummer company ID
approverNoagent: approved through a person's delegated API, CLI or MCP connection. auto_run: approved by a channel's auto-run setting
environmentYesEnvironment that owns the resource

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / approver / description
      Previous value: -"agent: approved through a person's delegated API, CLI or MCP connection"New value: +"agent: approved through a person's delegated API, CLI or MCP connection. auto_run: approved by a channel's auto-run setting"
    • changedInput schema / properties / approver / enum
      Previous value: -[
      -  "any",
      -  "person",
      -  "agent"
      -]New value: +[
      +  "any",
      +  "person",
      +  "agent",
      +  "auto_run"
      +]
  2. Added

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=true, so the trailing 'Read-only.' adds nothing. The description does contribute 'newest first' ordering and the fact that totals comparing agent calls with human decisions are included, which are behavioral facts not in the annotations, but it says nothing about pagination or how the default 'executed' filter changes the result set.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

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

The body is one long chained sentence of nested 'and ... and ...' clauses enumerating returned fields, duplicating the title almost verbatim and hard to parse. Only the front-loaded 'List published plans, newest first' is efficient; the rest is dense jargon that would benefit from bullets or being cut.

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

Completeness3/5

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

No output schema exists, so it is legitimate for the description to sketch return values, and it does so in detail. However, for a six-parameter paginated read tool it omits cursor/pagination behavior and how the cursor pattern works, leaving a real gap an agent will hit on the second page.

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 83% and four of six parameters are enums with their own descriptions, so the schema carries the parameter burden. The description's prose about approvals, auto_run and runs_as loosely maps to the approver/call filters but gives no filter syntax or enum guidance beyond what the schema already documents.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The opening clause 'List published plans, newest first' gives a specific verb, resource and ordering, so the agent knows exactly what it gets back. It does not differentiate from adjacent list tools such as summer_runs_list, summer_investigations_list or summer_cases_list, so it falls short of a 5.

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?

There is no statement of when to use this versus the many sibling list tools, and no prerequisites or exclusions beyond the implied 'published plans'. The agent must infer the usage context from the resource name alone.

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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