context-hub

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context_get

Search, read a stable reference, or inspect the public manifest to retrieve context from local JSONL/Markdown sources. Get source summaries and invocation markers.

Instructions

Search, read a stable ref, or inspect the public manifest. Responses include a context_hub invocation marker and source summary.

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": {
      "op": "<op>"
    },
    "name": "context_get"
  }
}

Input Schema

Name	Required	Description	Default
`op`	Yes
`ref`	No
`kinds`	No
`limit`	No
`query`	No
`cursor`	No
`max_chars`	No
`project_id`	No
`include_history`	No

Output Schema

Name	Required	Description	Default
`op`	Yes
`items`	No
`content`	No
`projects`	No
`context_hub`	Yes
`next_cursor`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 15, 2026

TDQS

B3.1/5.0

Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses that responses include a context_hub invocation marker and source summary, which is useful. However, it doesn't mention read-only vs mutating behavior, pagination, or error conditions, leaving the behavioral profile incomplete.

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?

The description is a single sentence that front-loads the three operations and adds a concrete response detail. It is compact and every clause earns its place, though it could be slightly more structured.

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

Completeness2/5

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

With 9 parameters, 0% schema coverage, no annotations, and no sibling context, the description is too thin. The output schema exists, so return values are covered, but the tool's selection criteria, parameter semantics, and behavioral traits are under-specified for an agent to invoke it confidently.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

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, but it only mentions 'stable ref' and 'public manifest' without explaining the parameters. The op enum is self-explanatory, but ref, kinds, limit, query, cursor, max_chars, project_id, and include_history are left entirely to the schema, which has no descriptions.

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 names three distinct operations (search, read, inspect manifest) and a stable ref concept, which is clear enough to distinguish the tool's purpose. However, it doesn't name any sibling tools, so differentiation relies on the op enum rather than explicit contrast.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage contexts by listing operations ('Search, read a stable ref, or inspect the public manifest'), but it doesn't state when to use one op over another or when to prefer an alternative tool. With no siblings and no exclusions, the guidance is adequate but implicit.

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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