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context-saver-mcp

context-saver-mcp

by renniyy
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Hybrid

Plan the minimal toolset for a task

cs_plan

Analyze a task to recommend the minimal downstream tools to load, returning ranked matches with reasons when tool selection is unclear.

Instructions

Inspect the user's task and recommend the minimal set of downstream tools to load. Scores the task against the whole catalog and returns ranked matches with reasons. Use when unsure which tools a task needs.

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": {
      "task": "<task>"
    },
    "name": "cs_plan"
  }
}

Input Schema

NameRequiredDescriptionDefault
taskYesThe user's task, verbatim

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.2

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full burden, and it does disclose the key behavior: the task is scored against the entire catalog and the result is ranked matches with reasons. It also implies a read-only advisory operation rather than an actual load. It omits cost/latency implications of catalog-wide scoring and does not state whether recommendations must then be applied via cs_load, leaving a modest gap.

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?

Three short sentences, front-loaded with the core action and followed by the return behavior and the usage cue. Nothing is redundant, though the second and third sentences could be merged without loss.

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 one-parameter, annotation-free analysis tool with no output schema, the description supplies what an agent needs: what it does, what comes back, and when to call it. The main missing piece is the handoff to cs_load after receiving recommendations, which the agent must infer.

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?

There is a single parameter with 100% schema description coverage ('The user's task, verbatim'), so the schema already does the work. The description's phrasing 'Inspect the user's task' reinforces but does not extend that meaning, which matches the baseline-3 guidance for high-coverage schemas.

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 description uses a specific verb+resource pair: 'recommend the minimal set of downstream tools to load,' and adds that it 'Scores the task against the whole catalog.' That is concrete enough to separate it from a plain load or discover operation. It stops short of naming a sibling explicitly, so it lands just below the top mark.

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?

'Use when unsure which tools a task needs' gives a clear trigger condition, which is exactly the decision point an agent faces before calling cs_load or cs_discover. There is no explicit when-not guidance or named alternative, but the context is unambiguous.

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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