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Compress Contexts

compress_contexts

Selects informative, diverse paragraphs within an approximate token budget to compress text while preserving key content.

Instructions

Choose informative, diverse paragraphs under an approximate text-token budget.

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": {
      "paragraphs": "<paragraphs>"
    },
    "name": "compress_contexts"
  }
}

Input Schema

Name	Required	Description	Default
`num_tokens`	No
`paragraphs`	Yes
`dedup_threshold`	No
`similarity_budget_threshold`	No
`long_paragraph_token_threshold`	No
`paragraph_summary_max_sentences`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 10, 2026

TDQS

C2.4/5.0

Behavior2/5

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

No annotations are provided, so the description carries the entire behavioral load, yet it only states the selection goal. It does not disclose deduplication behavior, how over-long paragraphs are summarized, whether ordering is preserved, whether the output is a subset of inputs, rate limits, or cost characteristics — all material for a tool whose name implies transformation.

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

Conciseness3/5

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

One front-loaded sentence with no filler or redundancy. However, brevity here comes at the cost of under-specification rather than being earned concision.

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?

An output schema exists so return values need not be explained, but for a six-parameter tool with no annotations and no parameter documentation, the description leaves far too much unstated. An agent cannot predict the effect of the threshold parameters or how the compression is performed.

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% across six parameters, several of which are opaque heuristic knobs (dedup_threshold, similarity_budget_threshold, long_paragraph_token_threshold, paragraph_summary_max_sentences). The description only alludes to a token budget, giving no meaning for the remaining controls, so it fails to compensate for the coverage gap.

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

Purpose3/5

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

The description gives a verb ('Choose') and object ('paragraphs') plus the selection criteria ('informative, diverse') and a budget constraint, so the gist is inferable. But it never says what 'compress' means operationally (selection only? dedup? summarization?) and gives no differentiation from the sibling 'compress_query_contexts', leaving ambiguity about scope.

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 when-to-use or when-not-to-use guidance, no mention of prerequisites, and no routing to alternatives such as deduplicate_texts, summarize_paragraphs, or compress_query_contexts. The agent must guess from the 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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