compaction-mcp

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Offload arbitrary text

offload_store

Stash large text outputs like logs, grep results, or API payloads as a blob and receive a digest plus handle, keeping the context window clean.

Instructions

Stash large text (command output, grep results, logs, API payloads) as a blob and return a digest + handle instead of putting it all in the window.

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": {
      "label": "<label>",
      "content": "<content>"
    },
    "name": "offload_store"
  }
}

Input Schema

Name	Required	Description	Default
`label`	Yes
`content`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 7, 2026

TDQS

A4/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the core behavior (store text, return digest + handle) but omits lifecycle details such as persistence, retrieval methods, size limits, or whether the stored content affects context state. This is a partial disclosure, leaving important behavioral gaps.

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 description is a single, well-structured sentence that front-loads the action, provides examples, and states the outcome. No extraneous words; every part earns its place.

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 simple store tool with no output schema, the description covers the main purpose, usage context, and return value. It doesn't mention how to retrieve the stored blob (though sibling tools exist) or any persistence rules, but these are arguably outside this tool's scope. Overall, it's sufficiently complete.

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 0%, so the description must compensate. It clarifies that 'content' is the large text being stashed, but does not explain the 'label' parameter's role or how it relates to the returned digest/handle. With only two simple string params, partial compensation is acceptable but not complete.

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, 'Stash,' and clearly states the resource (large text as a blob) and the outcome (return a digest + handle). It also gives concrete examples (command output, grep results, logs, API payloads) and distinguishes itself from siblings like read_offloaded and context_compact by explaining the benefit of avoiding window clutter.

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 implies when to use the tool: when you have large text that would otherwise occupy the window. It doesn't explicitly name alternatives or exclusions, but the context is clear enough for an agent to decide appropriately relative to siblings like context_compact or offload_fetch.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.