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Context & AI engineering

26,304 rows from 10,117 repositories

Making an agent good at your problem. The thing this whole site is about.

What Context & AI engineering skills agree on

1,865 skill files read, by 1,328 of the 2,349 authors on this shelf whose files we hold, 2026-09-06

The middle one of the 226 measured here is ~1.7k tokens long, counted with cl100k_base

Counted by distinct author, so one author publishing three of these counts once. Where a claim sits in fewer files than authors, that is said: a claim held by forty authors across three files is one file people copied, not forty people who agreed. Near-identical wordings are grouped and the other wordings are shown, so the grouping is yours to check.

What they tell the agent to do

  1. Dispatch a fresh subagent for each task76 of 1328 in 59 filesalso worded as dispatch a fresh implementer subagent for each task; dispatch a fresh implementer subagent per task
  2. Perform spec compliance review before code quality review44 of 1328 in 34 filesalso worded as perform spec compliance review first; Perform spec compliance review after each task
  3. Dispatch a final code reviewer after all tasks38 of 1328 in 26 filesalso worded as dispatch final reviewer after all tasks finish; use the final code reviewer after all tasks finish
  4. Answer subagent questions before allowing implementation36 of 1328 in 26 filesalso worded as Answer all subagent questions before implementation; answer all subagent questions before they begin work
  5. Use the least powerful model capable of the task33 of 1328 in 26 filesalso worded as use the least powerful model for mechanical tasks; use the least powerful model suitable for the task
  6. Create a TodoWrite list for all tasks32 of 1328 in 22 filesalso worded as create a todo list for all tasks; Create a TodoWrite list
  7. Perform a task review after each implementation31 of 1328 in 24 filesalso worded as perform a task review after each task; Perform code quality review after each task
  8. Extract all tasks and context from the plan29 of 1328 in 20 filesalso worded as extract all tasks and context from plan; extract all tasks and context before starting
  9. Provide full task text to subagents28 of 1328 in 20 filesalso worded as provide full task text and context to subagents; provide full task text and context to each subagent
  10. Use git worktrees for isolated workspaces25 of 1328 in 20 filesalso worded as use git worktrees for isolation; use git worktrees to ensure isolated workspaces
  11. Specify the model explicitly when dispatching a subagent23 of 1328 in 18 filesalso worded as explicitly specify the model when assigning subagents; specify models explicitly for each subagent
  12. Execute all tasks from the plan without stopping21 of 1328 in 16 filesalso worded as execute all tasks in the plan without pausing; execute all tasks in the plan without pausing for approval
  13. Verify robots.txt allows AI crawlers21 of 1328 in 7 filesalso worded as Verify AI bot access in robots.txt; Verify AI crawler accessibility and robots policies
  14. Monitor AI visibility monthly20 of 1328 in 6 filesalso worded as Monitor AI visibility and citation rates monthly
  15. Read product marketing context before starting20 of 1328 in 6 filesalso worded as Read product marketing context before asking questions; check product marketing context before starting

What they tell it not to do

  1. Do not dispatch multiple implementation subagents in parallel70 of 1328 in 53 filesalso worded as Dispatch multiple implementation subagents in parallel; never dispatch multiple implementation subagents in parallel
  2. Do not skip task reviews58 of 1328 in 42 filesalso worded as skip review loops; never skip review loops
  3. Do not make subagents read the plan file53 of 1328 in 41 filesalso worded as Do not make subagents read the plan file; never make subagents read the plan file
  4. Do not ignore subagent questions44 of 1328 in 32 filesalso worded as never ignore subagent questions; ignore subagent questions
  5. Never proceed with unfixed issues41 of 1328 in 27 filesalso worded as Do not proceed with unfixed issues; proceed with unfixed issues
  6. Do not start code quality review before spec compliance40 of 1328 in 30 filesalso worded as never start code quality review before spec compliance; never skip spec compliance or code quality reviews
  7. Do not start implementation on main branch without consent38 of 1328 in 32 filesalso worded as never start implementation on main branch without consent; do not use the main or master branch for implementation
  8. Never accept close enough on spec compliance34 of 1328 in 24 filesalso worded as do not accept close enough on spec compliance; accept close enough on spec compliance
  9. Never let self-review replace actual review31 of 1328 in 21 filesalso worded as let self-review replace external review; do not let implementer self-review replace actual review
  10. Do not pause to check in with human partner between tasks29 of 1328 in 24 filesalso worded as do not pause to check in with human partner; do not pause for human check-ins between tasks

What they expect to be installed

  1. git253 of 1328
  2. bash129 of 1328
  3. grep122 of 1328
  4. curl91 of 1328
  5. python390 of 1328
  6. claude83 of 1328 in 79 files
  7. node82 of 1328
  8. gh74 of 1328
  9. jq67 of 1328
  10. npm66 of 1328

What they ask it to produce

  1. SKILL.md47 of 1328also worded as SKILL.md file; draft SKILL.md
  2. Implemented code35 of 1328 in 25 filesalso worded as Adapted implementation code; implemented agent code
  3. CLAUDE.md33 of 1328also worded as Updated CLAUDE.md; CLAUDE.md updates
  4. Pull requests31 of 1328 in 24 filesalso worded as pull request; one pull request
  5. TodoWrite30 of 1328 in 20 filesalso worded as TodoWrite list
  6. AGENTS.md27 of 1328also worded as AGENT.md; AGENTS.md.bak
  7. Markdown report26 of 1328 in 24 filesalso worded as Markdown security report; markdown audit report
  8. AI visibility audit report24 of 1328 in 7 files

When Context & AI engineering authors say to reach for one

The situations these authors wrote into their own files, counted out of the same 1,328 authors, with the skills that name each one

How Context & AI engineering skills are built

17,957 skill directories by 3,594 authors, read from their repositories’ own file trees 2026-08-05

The middle bundle among those shipping files is 3 files, 19.4 KB beside SKILL.md

Counted by distinct author, same as above, so one author publishing forty template copies counts once. SKILL.md itself is not counted as a file, so a single-file skill is one where that file is the whole skill.

The shape

  1. SKILL.md is the whole skill1,002 of 3,594 authors, 8,446 of 17,957 skills
  2. files ship beside it2,592 of 3,594 authors, 9,511 of 17,957 skills
  3. executable scripts ship inside1,381 of 3,594 authors, 3,721 of 17,957 skills

The folders they converge on

  1. references/1,629 of 3,594 authors, 4,820 of 17,957 skills
  2. scripts/1,138 of 3,594 authors, 3,159 of 17,957 skills
  3. agents/689 of 3,594 authors, 1,334 of 17,957 skills
  4. assets/491 of 3,594 authors, 941 of 17,957 skills
  5. templates/261 of 3,594 authors, 431 of 17,957 skills
  6. examples/238 of 3,594 authors, 413 of 17,957 skills

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All 26,304 in the catalog