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Tool usage and response-size accounting

stats

Identify which MCP tool consumes context by tracking per-tool call counts and response sizes. Checkpoints let you isolate a single task's usage.

Instructions

Per-tool call counts and response sizes recorded to /.slimdex/stats.json. Reported in characters, not tokens — char/4 estimates are unreliable across tokenizers, so this measures what it can measure honestly. Use it to see which tool is actually producing your context, and to tune limits. Counters are CUMULATIVE across every session on this repo until reset. To measure ONE task: call checkpoint:true when you start, then session:true when you finish — the server is long-lived, so session:true alone means 'since the server booted', which can span several chats.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
resetNoClear ALL counters, including the repo's all-time history.
sessionNoReport what this process recorded since it started, or since the last checkpoint.
checkpointNoZero the session tally only (all-time history untouched). Call at the start of a task.
Behavior4/5

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

With no annotations, the description carries full responsibility. It discloses that counters are cumulative, explains the character-not-token choice, and clarifies the server-lifetime implication of session:true. It also reveals the file location. The main gap is that it doesn't state what happens with no flags, but overall transparency is high.

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 bit longer than average but every sentence adds value: core purpose, unit rationale, usage scenario, lifetime semantics, and a concrete recipe. It is well-structured and front-loaded with the main idea, earning a 4 rather than a 3, though not as tight as a two-sentence description.

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 tool with three boolean flags and no output schema, the description is quite complete. It covers the data source, units, persistence, and a specific workflow. The only notable omission is the default behavior when no flags are passed (whether it just reports current totals), but this is a minor gap given the schema implies optional flags.

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

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds value by explaining the relationship between checkpoint and session and how reset interacts with cumulative counters. This goes beyond simply restating schema fields, so a 4 is warranted.

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 clearly states that the tool provides per-tool call counts and response sizes, and its purpose is to see which tool is producing context. The verb 'use it to see' gives a functional role, but it doesn't explicitly state 'reports' or 'retrieves', and the resource is a stats file. It does distinguish from siblings by its accounting focus, but the lack of a direct command verb holds it back from a 5.

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 gives explicit when-to-use ('use it to see which tool is actually producing your context, and to tune limits') and provides a precise recipe for a one-task measurement (checkpoint:true then session:true). It doesn't mention when not to use it or alternatives, but the guidance covers the key scenarios. This is strong but not exhaustive enough for a 5.

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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