building-incident-response-dashboard

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.

Quality

75%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

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tessl review fix ./skills/building-incident-response-dashboard/SKILL.md

Quality

Content

61%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

Actionable and well-sequenced at the panel level, but it fails to route detail into the available reference/script bundle, inlines bulk SPL, and lacks validation checkpoints for its destructive/batch operations.

Suggestions

Add explicit validation/verification checkpoints to destructive and batch steps — e.g., confirm host isolation succeeded before scanning, and verify scheduled-search output before outputlookup overwrites the affected-systems lookup.

Link references/api-reference.md and scripts/agent.py from the relevant steps (e.g., 'See references/api-reference.md for splunk-sdk patterns and TheHive API') instead of leaving the bundle unreferenced.

Move the per-panel SPL bulk into a reference file (one level deep) and keep SKILL.md as an overview with concise key examples to cut token weight and improve navigation.

Dimension	Reasoning	Score
Conciseness	Mostly executable SPL with little padding, but the Key Concepts table and Common Scenarios section explain well-known terms (MTTD/MTTR) and add length that does not all earn its place.	3 / 5
Actionability	Provides copy-paste-ready SPL queries and Dashboard Studio XML covering the common dashboard panels, with concrete timeline CSV and output-format examples.	5 / 5
Workflow Clarity	Seven steps are clearly sequenced, but batch/destructive operations (scheduled outputlookup updates, enterprise IOC scans, host isolation) lack validation or verification checkpoints, capping this at 3.	3 / 5
Progressive Disclosure	The body is largely monolithic with all SPL inlined, and the existing references/api-reference.md and scripts/agent.py bundle files are never linked or signaled from the body, so content that belongs in separate files is inlined and references are buried.	2 / 5
	Total	13 / 20 Passed

Description

88%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description that names platforms, concrete capabilities, and an explicit 'Use when' trigger. Minor gains possible from richer trigger synonyms and sharper boundary language to reduce overlap with general SOC monitoring skills.

Dimension	Reasoning	Score
Specificity	Names three platforms (Splunk, Elastic, Grafana) and four concrete tracking actions ('affected systems, containment status, IOC spread, and response timeline'), matching the comprehensive-coverage anchor.	5 / 5
Completeness	Explicitly answers what it does (builds dashboards tracking specific items) and when to use it ('Use when IR teams need unified visibility during incident coordination and post-incident reporting').	5 / 5
Trigger Term Quality	Includes natural terms like 'incident response dashboards', 'SOC analysts', 'IR teams', 'incident coordination', and 'post-incident reporting', but lighter on synonyms and file/extension variants, so it sits below the comprehensive anchor.	4 / 5
Distinctiveness Conflict Risk	It carves a clear IR-dashboard niche, but 'incident response dashboards' still overlaps with adjacent SOC/dashboard skills, so it is mostly distinct rather than minimal-conflict.	4 / 5
	Total	18 / 20 Passed

Validation

93%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: mukul975/Anthropic-Cybersecurity-Skills
Path: skills/building-incident-response-dashboard/SKILL.md
Commit: 9429fe9

Reviewed: 2 days ago

Table of Contents

Discovery Implementation Validation

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