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search_fibre

Search the Celestia Fibre history kept by Cumulo (Mocha testnet, mocha-5), live: give a transaction hash, blob id or commitment, a block height, an account (celestia1...), a namespace, a validator (name, celestiavalcons1... or celestiavaloper1...) or a UTC day (YYYY-MM-DD) and get the blobs, events, validators or the daily totals that match, with the archive files of a day. Use it when you hold an identifier and do not know what it is. For the latest blobs or events without an identifier use list_fibre_blobs or list_fibre_events. Names in results are typed by validators and publishers and marked untrusted.

Input Schema

NameRequiredDescriptionDefault
qYesTransaction hash, blob id, commitment, height, account, namespace, validator or a UTC day (YYYY-MM-DD)
chainNoChain id; leave out for the one Cumulo monitors today (mocha-5, the Mocha testnet)
limitNoBlobs and events to show per kind

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does add real context: the data is live, the default chain is mocha-5, a day query also returns archive files, and result names are typed by validators/publishers and marked untrusted. It omits operational traits such as auth requirements or rate limits, so it is strong but not exhaustive.

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 the verb and resource, then usage routing, then a trust caveat at the end. The opening sentence is long and repeats the identifier list already in the schema, but every remaining clause carries information and there is no filler.

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 or annotations exist, yet the description names the return kinds (blobs, events, validators, daily totals, archive files) and flags the trust status of returned names. Missing only secondary details like rate limits and pagination behavior for limit, so it is nearly complete for a live search tool.

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 all three parameters (q, chain, limit) are already documented in the schema. The description largely restates the q identifier list and the mocha-5 default rather than adding syntax or format detail beyond the schema, which is the baseline-3 case.

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 (Search) and resource (Celestia Fibre history kept by Cumulo on mocha-5) and enumerates exactly what can be supplied as the query. It also explicitly disambiguates from the sibling list tools (list_fibre_blobs, list_fibre_events), so an agent can route without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit when-to-use condition ('when you hold an identifier and do not know what it is') and a when-not with the named alternatives for the no-identifier case. Nothing about selection is left to inference.

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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