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ZeroWidth Ledger

List metric feeds

ledger_feeds_list
Read-only

The standing instructions for how metrics' numbers arrive — which tool each one calls, how often, and how the last run went. Check before proposing a feed so you don't duplicate one, and consult when a user asks why a metric is stale: a feed with a failing last run is usually the answer.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
metricIdNoNarrow to one metric (id or slug).
workspaceNoWorkspace slug. Omit to use the pinned workspace.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=false, so the safety profile is fully covered. The description adds the useful fact that each feed carries a last-run status, which explains its diagnostic value, but says nothing about ordering, pagination, or result size. With annotations carrying the safety burden, this is adequate but not rich.

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, no filler, with the resource definition front-loaded ahead of the usage guidance. The em-dash clause packing three attributes is dense but informative. Slightly indirect opening (a noun phrase rather than a verb phrase) costs it the top score.

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?

No output schema exists, so the description must convey what a feed record contains, and it does name the key fields (target tool, cadence, last-run outcome). With only two optional, fully documented parameters and complete safety annotations, an agent has what it needs to call this correctly; ordering and pagination behavior are the only real omissions.

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 description coverage is 100%, so both parameters (metricId as id-or-slug narrowing, workspace with pinned-workspace default) are already fully documented in the schema. The description adds no parameter detail at all, which is the expected baseline when the schema does the heavy lifting.

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 defines the resource concretely and specifically: 'the standing instructions for how metrics' numbers arrive — which tool each one calls, how often, and how the last run went.' That is enough for an agent to distinguish metric feeds from sibling families like ledger_entries_*, ledger_feeds_create/run, and ledger_metrics_list. It never states the verb 'list' explicitly, relying on the title for that, which keeps it just short of 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?

It gives two concrete triggers: check before proposing a feed to avoid duplication, and consult when a user asks why a metric is stale because a failing last run is usually the cause. That is unusually actionable guidance for a list tool. It does not name competing tools (e.g. ledger_feed_sources_list or ledger_feeds_preview) as alternatives, so no explicit when-not routing.

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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