Epovest

Read the canon of a project and its history

get_canon

Read-onlyIdempotent

The brand canon of a project and every revision it went through. canon is the CURRENT wording, under the same keys update_project_canon writes (one_liner, short, long, category, language, perks, website, legal_name, address, phone, whatsapp, email), and canon_version its number. history carries each version newest first, with its author, its date, and changes, the fields that version touched with their before and after values. Reach for it to RE-PROPAGATE a revision: get_logbook says a canon moved to a version and which keys it touched, this says what the old wording was, which is the string to find on a page and replace, and what the new one is. Values come back raw, so perks is the ordered list and language the short code. On a project whose canon is not posted yet, history is empty and canon_version is null.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`project_id`	Yes	UUID of the project: call list_projects to find it.

TDQS

A4.7/5.0

Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is known. The description adds rich behavioral context: return structure (canon keys, canon_version, history newest-first with author/date/changes), raw value formats (perks as ordered list, language short code), and the null/empty behavior for unposted canons. It goes well beyond what annotations provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, then progressively layers structure and usage. Every sentence carries unique information—no fluff. It is longer than average but each clause earns its place by explaining return fields or the re-propagation workflow.

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, but the description thoroughly explains what the agent will receive: the canon object with specific keys, canon_version, history array with author/date/changes, and raw value semantics. It also covers the edge case. For a read-only tool with strong annotations, nothing important is missing.

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?

The schema covers the only parameter (project_id) with a description and format, and points to list_projects. The description does not add anything about the parameter beyond that, which is acceptable given 100% schema coverage. Baseline 3 is appropriate.

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?

The description opens with a clear verb ('Read') and resource ('the canon of a project and its history'), and immediately distinguishes it from get_logbook by explaining that this returns the canon's history and is used for re-propagation. This makes the tool's unique purpose unambiguous even among 50+ siblings.

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?

It explicitly names when to use it: 'Reach for it to RE-PROPAGATE a revision' and explains the relationship to get_logbook (which says a canon moved to a version and which keys it touched). It also covers the edge case when canon is not posted. This gives the agent concrete decision rules.

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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TDQS

A4/5.0

Disambiguation4/5

Each tool maps to a distinct resource and action, and the descriptions go out of their way to separate near-neighbor concepts like surfaces vs corroborations and score series vs raw responses. A few related pairs (get_results/get_responses, get_credits/get_usage, create_surface/create_corroboration) could still be confused at a glance, so it is not a perfect 5.

Naming Consistency5/5

Tool names follow a highly consistent verb_noun snake_case pattern across all 67 tools, with clear families like create_, update_, get_, list_, archive_, restore_, and delete_. Minor quirks such as topup_credits as one word do not break the overall uniformity.

Tool Count1/5

67 tools is an extreme count for a single MCP server, even for a broad brand-monitoring domain. The surface is bloated with lifecycle variants per entity, and the sheer number makes the server hard to navigate and prompt against.

Completeness5/5

The server covers full lifecycles for projects, trackers, surfaces, corroborations, quests, logbook entries, keyword discoveries, competitor scans, link targets, sources, support, and billing. Archive/restore and soft-delete paths prevent dead ends, and nearly every obvious workflow has a corresponding tool.

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