Builds real-time incident response dashboards in Splunk, Elastic, or Grafana to provide SOC analysts and leadership with situational awareness during active incidents, tracking affected systems, containment status, IOC spread, and response timeline. Use when IR teams need unified visibility during incident coordination and post-incident reporting.
70
63%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/building-incident-response-dashboard/SKILL.mdQuality
Discovery
100%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 an excellent skill description that clearly articulates specific capabilities (building IR dashboards in named platforms), concrete tracked metrics (affected systems, containment status, IOC spread, response timeline), target audience (SOC analysts, leadership), and explicit trigger conditions. It uses proper third-person voice and provides enough specificity to be clearly distinguishable from adjacent skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions and outputs: 'builds real-time incident response dashboards', tracking 'affected systems, containment status, IOC spread, and response timeline', across specific platforms (Splunk, Elastic, Grafana), for specific audiences (SOC analysts and leadership). | 3 / 3 |
Completeness | Clearly answers both 'what' (builds real-time IR dashboards in specific platforms tracking specific metrics) and 'when' (explicit 'Use when IR teams need unified visibility during incident coordination and post-incident reporting'). | 3 / 3 |
Trigger Term Quality | Includes strong natural trigger terms users would say: 'incident response', 'dashboard', 'Splunk', 'Elastic', 'Grafana', 'SOC', 'containment status', 'IOC', 'situational awareness', 'incident coordination', 'post-incident reporting'. These cover the domain well with terms practitioners actually use. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive niche combining incident response + dashboarding + specific SIEM/observability platforms. Unlikely to conflict with general dashboarding skills or general security skills due to the specific combination of IR context, named platforms, and SOC-specific terminology. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
27%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill provides a comprehensive collection of Splunk SPL queries for incident response dashboards but suffers from excessive verbosity, including glossary definitions and tool descriptions that Claude doesn't need. It lacks validation checkpoints in its workflow and fails to deliver on its promise of multi-platform support (Elastic, Grafana). The monolithic structure with no progressive disclosure makes it token-inefficient.
Suggestions
Remove the Key Concepts glossary, Tools & Systems descriptions, and Common Scenarios sections — these explain things Claude already knows and waste tokens. Move them to a separate reference file if needed.
Add validation steps after each panel build (e.g., 'Run the query standalone first to verify results before embedding in dashboard; check that lookup files exist with `| inputlookup ir_affected_systems.csv | head 5`').
Split platform-specific content into separate files (e.g., SPLUNK_DASHBOARD.md, ELASTIC_DASHBOARD.md, GRAFANA_DASHBOARD.md) and keep SKILL.md as a concise overview with links.
Either provide concrete Elastic/Grafana examples or remove the multi-platform claim from the skill to avoid misleading guidance.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is extremely verbose at ~200+ lines with significant padding. The 'When to Use' section, 'Key Concepts' glossary (defining MTTD/MTTR which Claude knows), 'Tools & Systems' descriptions, and 'Common Scenarios' sections all add tokens without actionable value. The CSV example data, while illustrative, is lengthy. Much content explains concepts Claude already understands. | 1 / 3 |
Actionability | The SPL queries are concrete and mostly executable, but many rely on lookup files (ir_affected_systems.csv, ir_timeline.csv, ir_ioc_list.csv) that must pre-exist without guidance on creating them. The Dashboard Studio XML is a skeleton with makeresults (mock data) rather than real data integration. The skill claims to support Elastic and Grafana but only provides Splunk examples. | 2 / 3 |
Workflow Clarity | Steps are sequenced logically (design layout → build panels → automate), but there are no validation checkpoints. No step verifies that queries return expected results, that lookups are properly formatted, or that the dashboard renders correctly. For a multi-step process involving dashboard construction with data dependencies, the absence of validation/testing steps is a notable gap. | 2 / 3 |
Progressive Disclosure | This is a monolithic wall of content with no references to external files. The Key Concepts table, Tools & Systems list, Common Scenarios, and Output Format sections could all be separate reference files. Everything is inline, making the skill very long. There are no links to supplementary materials for Elastic/Grafana alternatives or detailed IOC management. | 1 / 3 |
Total | 6 / 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 | |
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Table of Contents
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