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delimit_diagnose

Run a comprehensive health check of the Delimit installation to diagnose connectivity, dependencies, governance, permissions, API keys, network, version, daemons, and disk issues.

Instructions

Comprehensive health check of the Delimit installation (delimit doctor).

When to use: as the universal first-step diagnostic when something isn't working — covers MCP connectivity, deps, governance state, AI assistants, permissions, API keys, network, version, daemons, disk. When NOT to use: for repo-level health (use delimit_repo_diagnose) or first-run discovery (delimit_quickstart).

Sibling contrast: delimit_repo_diagnose checks one repo; this checks the Delimit installation as a whole.

Side effects: in normal mode, fixes some configuration drift (writes a doctor-manifest.json so later --undo can revert). dry_run=True is read-only and previews changes. undo=True reverts changes from the last doctor run using the saved manifest.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_pathNoProject to diagnose. Default "." (cwd)..
dry_runNoIf True, preview changes without executing.
undoNoIf True, revert changes from the last run.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses side effects: normal mode fixes configuration drift and writes a manifest, dry_run is read-only, and undo reverts changes. This is good, but could be more explicit about permissions or data scope.

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?

Well-structured with clear labeled sections (When to use, When NOT to use, Sibling contrast, Side effects). Every sentence adds value without redundancy. Length is appropriate for the complexity.

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?

Given that an output schema exists, the description adequately covers purpose, usage, side effects, and parameter behavior. It mentions the areas checked (MCP connectivity, deps, governance, etc.), providing a complete picture for a diagnostic tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, giving baseline 3. The description adds value by explaining the effects of dry_run and undo in the 'Side effects' section, and noting the default for project_path. This goes beyond the schema descriptions.

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 is a comprehensive health check of the Delimit installation ('delimit doctor'), using a specific verb and resource. It distinguishes itself from sibling tools like delimit_repo_diagnose (repo-level) and delimit_quickstart (first-run), making its purpose unambiguous.

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?

Explicitly provides when to use (universal first-step diagnostic for installation-wide issues) and when NOT to use (repo-level health or first-run discovery), including specific alternative tool names. This gives clear, actionable guidance for selection.

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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