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Graphicle-AI

Graphicle MCP Server

Official

graph_history_stats

Read-onlyIdempotent

Summarize a repository's graph-history storage and timing: table row counts and content bytes, episodes, recent coverage uploads, change-impact report time, and active retention defaults.

Instructions

Storage and timing summary for a repository's graph history: row counts and content bytes per table (nodes, edges, edge_sources, coverage, cross_edges, unresolved_calls), episode count, recent coverage uploads with their format and granularity, the latest change-impact report's wall-clock time, and the retention defaults in force.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already establish the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's job is to add context, and it does: it discloses the exact content of the summary including retention defaults and the latest change-impact wall-clock time. It stops short of saying whether results are cached, how expensive the call is, or how repo selection defaults.

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?

One dense sentence, front-loaded with the summary category ('Storage and timing summary') before the content list. It is long but every clause maps to a real output element; the parenthetical table enumeration is the only mildly heavy part.

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?

With no output schema and no annotations covering return content, the description carries the full burden of describing what comes back, and it does so field-by-field. A read-only, single-optional-param tool needs little more; only the repo-default behavior and the stat-selector absence remain unstated.

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 single 'repo' parameter has 0% schema description coverage and the description only implies it via 'a repository's graph history'. It does not state the accepted identifier form, nor that the parameter is optional, nor what happens when it is omitted (presumably the current/default repo), so it only partially compensates for the schema gap.

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 names a specific resource (a repository's graph history) and enumerates exactly what is summarized: per-table row counts and byte sizes, episode count, coverage uploads, change-impact timing, and retention defaults. It is clearly not a query or mutation tool, but it never names the sibling graph_stats to distinguish history-oriented storage/timing stats from live graph stats.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no prerequisites, and no mention of alternatives such as graph_stats, graph_episodes, or repository_status. The agent must infer that this is a diagnostic/introspection call from the content list alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.