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Get caliber market snapshot

get_market_snapshot
Read-only

Caliber-level price distribution (median, p25, p75, min, max) over a rolling window. Purely descriptive statistics with methodology and sample counts; never a forecast or recommendation. Accepts the canonical caliber name or a common alias (for example "5.56" or ".223" for ".223/5.56"); list_calibers gives the canonical names. Returns error_v1 NOT_FOUND when no snapshot exists for the caliber/window. When extremaSuppressedByPolicy is true, min, max and both segments.*.min / segments.*.max are null BY POLICY rather than for lack of data: that caliber's published extremes are withheld pending revalidation. The median, quartiles, p95, segment medians and counts remain valid and complete — p95 is a percentile over the whole window rather than a single observation, so it is not withheld. Do not infer or substitute a floor for those calibers, and do not treat p95 as a stand-in for the withheld max. This is distinct from dataStatus: "INSUFFICIENT_DATA", which means the sample was too thin to compute anything.

Input Schema

NameRequiredDescriptionDefault
caliberYesCanonical caliber or a common alias, e.g. "9mm", "5.56". See list_calibers.
windowDaysNoRolling window in days. 7 or 30; defaults to 30.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / caliber / description
      Previous value: -"Canonical caliber, e.g. \"9mm\"."New value: +"Canonical caliber or a common alias, e.g. \"9mm\", \"5.56\". See list_calibers."
  2. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Goes well beyond readOnlyHint by disclosing the NOT_FOUND error contract, the extremaSuppressedByPolicy null semantics, which fields are still valid under suppression, and the distinction from dataStatus INSUFFICIENT_DATA. It also states the tool is descriptive only, never a forecast, which prevents misuse of the numbers.

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?

Front-loaded with purpose, then policy caveats in descending importance. Slightly long, but nearly every clause carries non-obvious information (suppression behavior, p95 caveat, error type); only the p95 explanation is somewhat verbose.

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

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, and the description compensates by naming the returned fields (median, p25/p75, min/max, p95, segments, counts, dataStatus) and explaining their edge-case behavior. Nothing needed to interpret or call the tool correctly is missing.

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 already 100%, so baseline is 3; the description adds alias examples ("5.56" / ".223" mapping to ".223/5.56") that clarify the caliber matching rule beyond the schema's short hint. It does not elaborate on windowDays, which the schema already constrains.

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

Purpose5/5

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

States a specific verb and resource in the first clause: caliber-level price distribution with the exact statistics returned. It is clearly distinguishable from list_calibers (referenced as the naming helper) and search_offers (this is descriptive aggregation, not offer lookup).

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?

Gives concrete routing help: use list_calibers for canonical names, aliases accepted, and what an error result means. It does not explicitly contrast when to choose this over search_offers for the same caliber, which keeps it below 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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