DevTune MCP

devtune_get_recent_answer_fetches

Read-onlyIdempotent

Get up to 20 latest answer-fetch hourly records in the selected UTC window. Each item is one rollup record, not an individual event or a whole-window total. hour_bucket is the start of an hour. verified_event_count confirms the claimed operator by peer address or Web Bot Auth signature; verified_by_signature_event_count is the part of verified_event_count a signature verified, and null when the method was not recorded for some verified requests in the record (requests stored before DevTune began recording it have none); failed_event_count contradicts the claimed operator; unknown_no_address_count means the sensor supplied no address; unknown_no_contract_count means the operator publishes no supported identity-checking contract; unknown_check_unavailable_count means a published check could not complete. The before-verification remainder is event_count minus those five counts.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "devtune_get_recent_answer_fetches"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No	Maximum hourly records, 1-20. Defaults to 20.
`windowDays`	No	Fixed rolling window in days: 7, 30, or 90. Defaults to 30.

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 9, 2026

TDQS

A3.6/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so this is bonus territory — and the description adds genuinely useful behavioral context: null semantics for verified_by_signature_event_count, legacy records predating method recording, and an explicit formula for the unverified remainder. It stops short of return shape/pagination detail, but the field-level disclosure is rich.

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?

Purpose is front-loaded, but the remainder is a single dense run-on sentence stringing six field definitions together with semicolons. The content earns its place, but formatting as a flat block hurts scannability and makes field semantics easy to lose.

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?

With no output schema, the description carries the full burden of explaining return values — and it does so field by field, including nullability and legacy-data caveats. What's missing is spatial/window framing beyond 'UTC window' and any hint at ordering or pagination, so an agent still guesses at some result-shape details.

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 coverage is 100%, so limit (1–20, default 20) and windowDays (7/30/90, default 30) are already fully documented in the schema. The description only echoes the window concept ('selected UTC window', 'hour_bucket is the start of an hour') without adding syntax or edge-case guidance. Baseline 3 is correct.

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?

States a specific verb and resource ('Get ... latest answer-fetch hourly records') with an explicit cap ('up to 20') and scope ('selected UTC window'). It also rules out two plausible misreadings ('not an individual event or a whole-window total'), which helps distinguish it from event-level siblings, though it never names an alternative tool.

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?

Usage context is implied through the record-granularity clarification, but there is no explicit 'use this when' clause and no named alternative (e.g. against devtune_get_visits_per_answer_fetch or devtune_get_search_rollups). The agent must infer selection from the granularity caveat 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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