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croc100

litescope

Inspect database health

litescope_health
Read-onlyIdempotent

Inspect SQLite, D1, or Turso databases for corruption, WAL bloat, freelist fragmentation, and reachability issues. Returns a JSON report with issue severity.

Instructions

Inspect a SQLite or D1 database for operational faults: corruption (PRAGMA integrity check), WAL bloat from a starved checkpoint, freelist fragmentation, and reachability. Returns a JSON report with a severity (ok / warning / critical) and a list of issues. Read-only.

For D1: set CLOUDFLARE_API_TOKEN + CLOUDFLARE_ACCOUNT_ID and use source=d1://DB_ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deepNoUse the exhaustive integrity_check instead of the faster quick_check
sourceYesDatabase source: a local file path (./app.db), a Cloudflare D1 DSN (d1://DB_ID when CLOUDFLARE_API_TOKEN+CLOUDFLARE_ACCOUNT_ID are set, or d1://TOKEN@ACCOUNT_ID/DB_ID), or a Turso DSN (turso://TOKEN@ORG/DB).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
issuesNoDetected problems (empty when healthy).
severityYesOverall verdict.
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral context: lists specific integrity checks, output format (JSON with severity and issues), and environment variable requirements for D1. This goes 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.

Conciseness4/5

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

The description is two paragraphs with no wasted words. The first paragraph covers purpose and output; the second covers D1 setup. It is efficient, though the D1 instruction could be integrated into the parameter description for better structure.

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 an output schema present, the description does not need to detail return values. It covers the core purpose, specific checks, and important usage notes (environment variables, source format). Missing is guidance on error handling or performance, but it is fairly complete for a health inspection 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 coverage is 100%, so the description does not need to add parameter details. It mentions source examples (d1://DB_ID) but does not clarify the 'deep' boolean or format requirements beyond the schema. 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 clearly states it inspects SQLite/D1 database health for specific faults (corruption, WAL bloat, freelist fragmentation, reachability). The verb 'inspect' and resource 'database health' are specific, and the listed checks distinguish it from sibling tools like litescope_locks or litescope_fleet_health.

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?

The description notes it is read-only and provides setup instructions for D1 sources. However, it does not explicitly state when to use this tool versus alternatives or when not to use it (e.g., for non-health queries). The context is clear but lacks exclusion guidance.

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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