datadog-automation
Automate Datadog tasks via Rube MCP (Composio): query metrics, search logs, manage monitors/dashboards, create events and downtimes. Always search tools first for current schemas.
75
66%
Does it follow best practices?
Impact
89%
1.28xAverage score across 3 eval scenarios
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/all-skills/skills/datadog-automation/SKILL.mdQuality
Discovery
82%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong description that clearly enumerates specific Datadog operations and includes excellent natural trigger terms. Its main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know precisely when to select this skill. The procedural note about searching tools first is a nice operational detail.
Suggestions
Add an explicit 'Use when...' clause, e.g., 'Use when the user asks about Datadog monitoring, log searches, metric queries, alert management, or dashboard configuration.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'query metrics, search logs, manage monitors/dashboards, create events and downtimes.' Also includes a procedural instruction to 'search tools first for current schemas.' | 3 / 3 |
Completeness | Clearly answers 'what does this do' with specific Datadog actions, but lacks an explicit 'Use when...' clause or equivalent trigger guidance. The when is only implied by the domain context. | 2 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'Datadog', 'metrics', 'logs', 'monitors', 'dashboards', 'events', 'downtimes', 'Rube MCP', 'Composio'. These cover the main terms a user working with Datadog would naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive due to the specific combination of 'Datadog', 'Rube MCP (Composio)', and the enumerated Datadog-specific operations. Unlikely to conflict with other skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
50%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a comprehensive reference for Datadog automation via Rube MCP that covers many workflows with clear structure and useful pitfall warnings. However, it suffers from redundancy (pitfalls repeated in sections and summary), lacks fully executable examples showing actual tool invocations, and misses validation/confirmation steps for destructive operations. The content would benefit from being split across multiple files given its length.
Suggestions
Add concrete, executable examples showing actual MCP tool calls with realistic parameters and expected response structures for at least 2-3 key workflows (e.g., querying metrics, creating a monitor).
Add explicit validation/confirmation checkpoints before destructive operations like DATADOG_DELETE_DASHBOARD (e.g., 'Confirm dashboard ID and title with user before deletion') and for creating indefinite downtimes.
Consolidate the duplicated pitfalls—remove the 'Known Pitfalls' summary section or remove per-workflow pitfalls, keeping information in only one place to reduce token usage.
Split detailed per-workflow parameter references and pitfalls into a separate REFERENCE.md file, keeping SKILL.md as a concise overview with quick-start examples and navigation links.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is reasonably well-organized but contains significant redundancy—pitfalls are repeated across sections and then again in a 'Known Pitfalls' summary section. The quick reference table duplicates information already covered in each workflow section. Some parameter descriptions are somewhat verbose for what Claude already knows. | 2 / 3 |
Actionability | The skill provides tool names, parameter lists, and some query syntax examples, but lacks fully executable end-to-end examples showing actual MCP tool calls with concrete arguments and expected responses. The monitor query syntax examples are helpful but most workflows describe what to do abstractly rather than showing copy-paste-ready invocations. | 2 / 3 |
Workflow Clarity | Workflows are clearly sequenced with numbered steps and labeled as Required/Optional, which is good. However, there are no validation checkpoints or feedback loops—for destructive operations like DELETE dashboard or creating downtimes without end times, there's no explicit 'confirm before proceeding' or verification step. The setup section has a good validation flow though. | 2 / 3 |
Progressive Disclosure | The content is a monolithic single file with no bundle files to reference. For a skill this long (~200+ lines covering 6 workflows), the detailed parameter lists and pitfalls for each workflow could be split into separate reference files. The structure within the file is decent with clear headers, but everything is inline. | 2 / 3 |
Total | 8 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- davepoon/buildwithclaude
- Commit
d065ead
- Reviewed
Table of Contents
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