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Machinepulse

Pulse

pulse

Snapshot every observatory metric for a day — window values with formula, formula_plain (one English line), basis, and per-metric history depth (metric_history_from); insufficient history is reported as a fact, never a fake zero. Use when the user asks for the current state of the AI agent ecosystem.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
as_ofNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior4/5

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

No annotations are supplied, so the description must carry the behavioral burden, and it does add non-obvious traits: what a snapshot contains, that history depth is per-metric, and the integrity guarantee that 'insufficient history is reported as a fact, never a fake zero.' It never states side-effect-freedom or error behavior explicitly, but the read-only character is strongly implied by 'snapshot ... for a day.'

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?

Two sentences: the first front-loads what the tool returns, the second gives the trigger. The semicolon-heavy middle clause is dense with domain jargon, but nothing is padded or redundant.

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

Completeness3/5

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 re-explained, and the description covers purpose, trigger, and data-integrity semantics. What is missing is call-critical detail: the as_of format and any boundary against the many overlapping summary/market tools.

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?

The single parameter as_of has zero schema description coverage, so the description must compensate. 'For a day' hints that as_of selects a date and implies day granularity, but it never names the parameter or gives the accepted format (ISO date, relative expression, timezone), which an agent needs in order to call it correctly.

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 states a specific verb and scope: 'Snapshot every observatory metric for a day,' enumerating the returned surface (window values, formula, formula_plain, basis, metric_history_from). It is far clearer than the opaque name/title 'Pulse'. It does not, however, explicitly distinguish itself from lookalike siblings such as market_overview, leaderboard, or the get_*_summary family.

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?

'Use when the user asks for the current state of the AI agent ecosystem' supplies a trigger, but it largely restates the purpose rather than routing. With 15 siblings, several of which plausibly answer a 'current state' question, no when-not conditions or named alternatives are given.

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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