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by io.github.cavan1977
OverviewDiscussionsAdmin

plan_context_window_budget

Given a set of MCP servers and their tool counts, show for every model context window (128K, 200K, 1M, 10M) how much of the window the tool definitions consume, how much is left for conversation, and whether the server set fits at all. Answers "how many servers can I attach on model X?".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
serversYesJSON array of {name, toolCount, avgTokensPerTool?} — e.g. [{"name":"github","toolCount":35}]. Accepts a JSON array, or a JSON string containing one.
avgTokensPerToolNoDefault tokens per tool definition when a server omits it (default 550)
reserveForOutputNoTokens to reserve for the model response (default 8000)
conversationShareNoFraction of the window you want left for human/agent conversation, 0-1 (default 0.25)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / servers / description
      Previous value: -"JSON array of {name, toolCount, avgTokensPerTool?} — e.g. [{\"name\":\"github\",\"toolCount\":35}]"New value: +"JSON array of {name, toolCount, avgTokensPerTool?} — e.g. [{\"name\":\"github\",\"toolCount\":35}]. Accepts a JSON array, or a JSON string containing one."
    • changedInput schema / properties / servers / type
      Previous value: -"string"New value: +[
+  "string",
+  "array",
+  "object"
+]
  2. First observed

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description must carry the burden of behavioral disclosure. It does reveal what the tool computes (per-window consumption, remaining space, fit). However, it doesn't state that this is a read-only estimation, how aggregate assumptions like avgTokensPerTool are used, or what the returned shape looks like.

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 two sentences with no filler; core behavior is front-loaded and the clarifying question adds value compactly. Every clause 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 read-only planning/calculation tool, the description covers the main outputs and the motivating use case well. It is slightly thin on assumptions and return format, but the schema defaults and parameter documentation fill most gaps.

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?

The schema already documents all four parameters and the servers input shape with 100% coverage, so the description adds little concrete parameter meaning. It provides helpful framing ('tool definitions consume', 'left for conversation') but not enough to exceed the baseline for high schema coverage.

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 ('show') and resource (MCP server tool definitions against model context windows), and lists exact outputs: consumed tokens, remaining capacity, and fit. It also states a concrete user question it answers. However, it does not explicitly distinguish itself from similar siblings like plan_mcp_token_budget or estimate_mcp_context_budget.

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 motivating question 'how many servers can I attach on model X?' implies a clear use casechers. But the description gives no explicit guidance on when to use this tool versus alternatives, and it does not mention exclusions or sibling relationships.

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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