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dokploy_github_update

dokploy_github_update
Idempotent

Update GitHub integration settings in Dokploy to manage application deployments and source code connections for self-hosted PaaS infrastructure.

Instructions

[github] github.update (POST)

Parameters:

  • githubId (string, required)

  • name (string, required)

  • gitProviderId (string, required)

  • githubAppName (string, required)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
githubIdYes
nameYes
gitProviderIdYes
githubAppNameYes
Behavior3/5

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

Annotations provide key behavioral hints: readOnlyHint=false (mutation), destructiveHint=false (safe), idempotentHint=true (repeatable), openWorldHint=true (broad scope). The description adds no behavioral context beyond these annotations—no mention of side effects, permissions, or response format. Since annotations cover core traits adequately, the description's lack of additional context results in a baseline score.

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 brief and structured with a clear header and parameter list. However, the first line '[github] github.update (POST)' is redundant with the tool name and title, and the parameter listing adds little value without explanations. It's concise but under-informative rather than efficiently packed with insights.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 4 parameters with 0% schema coverage, no output schema, and annotations that don't explain parameter purposes or mutation details, the description is incomplete. It doesn't clarify what the tool updates (e.g., GitHub provider settings), what the parameters mean, or what the outcome is. For a mutation tool with undocumented inputs, this is insufficient.

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

Parameters2/5

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

Schema description coverage is 0%, so the schema provides only names and types without meanings. The description lists parameter names but adds no semantic explanation (e.g., what 'githubId' refers to, what 'gitProviderId' is, or how 'githubAppName' is used). This fails to compensate for the schema's lack of descriptions, leaving parameters ambiguous.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description restates the tool name ('github.update') without clarifying what specific GitHub resource is being updated or what fields are modified. It lists parameters but doesn't explain the action's purpose beyond the tautological 'update'. Compared to siblings like 'dokploy_github_testConnection' or 'dokploy_github_getGithubRepositories', it lacks differentiation.

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

Usage Guidelines1/5

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

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., existing GitHub provider), when-not-to-use scenarios, or related tools like 'dokploy_github_create' or 'dokploy_github_testConnection'. This leaves the agent guessing about appropriate contexts.

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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