Map and assess documentation sources for accuracy, freshness, completeness, and discoverability.
npx skills add https://github.com/tonone-ai/tonone --skill atlas-recon
Please help me install this Agent Skill. Skill: atlas-recon Source: https://github.com/tonone-ai/tonone/tree/main/team/atlas/skills/atlas-recon Command: npx skills add https://github.com/tonone-ai/tonone --skill atlas-recon
Map and assess all documentation sources across the workspace for accuracy, freshness, completeness, and discoverability.
Run a documentation reconnaissance to map all docs and identify gaps in the knowledge base.
High-intent search queries and answers about installing and using this skill.
Documentation freshness is evaluated by detecting all sources and assessing each for accuracy and staleness. The assessment highlights stale docs and broken links across README files, ADRs, and inline docs to ensure knowledge base validity.
The best way to assess discoverability and completeness is to run a reconnaissance that maps all documentation sources and evaluates quality. This identifies tribal knowledge, single points of knowledge, and broken links following standard governance practices.
Documentation reconnaissance works for API specs and setup guides by detecting sources across docs directories, inline docs, and ADRs. It evaluates accuracy, freshness, completeness, and discoverability to map gaps and present a coverage risk assessment.
Use a documentation assessment instead of manual review when you need to detect sources across an entire workspace and map critical knowledge gaps in data models or onboarding materials. It provides a structured coverage and risk assessment following governance practices.
micaelmaltaAutomate creation and synchronization of README, API docs, ADRs, and inline comments.
williamzujkowskiScan Markdown files for broken cross-references and report remediation steps.
cdalsoniiiAudit documentation freshness by comparing modification dates against code changes.
rarestgReviews agent skills for quality, completeness, correctness, and unnecessary token consumption.
