From kernel
Unified entry point for new and resumed work. Classifies tasks, loads relevant skills, and guides through research, scope, and execution phases.
How this skill is triggered — by the user, by Claude, or both
Slash command
/kernel:ingestThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
<skill id="ingest">
Authority order (highest wins) — a manifest is a map, not the territory:
<skill_load> always: skills/debug/SKILL.md on_classify: bug: skills/debug/SKILL.md feature: skills/build/SKILL.md, skills/architecture/SKILL.md refactor: skills/architecture/SKILL.md review: skills/review/SKILL.md on_domain: frontend: skills/frontend/SKILL.md app: skills/app-dev/SKILL.md on_tier: 2+: skills/orchestration/SKILL.md reference: skills/build/reference/build-research.md </skill_load>
<on_start>
agentdb read-start
ls _meta/research/ # check prior work
Load /kernel:quality, /kernel:testing, /kernel:git immediately. After classify: load task-specific skills above. Do NOT proceed without loading them. After scope: if tier 2+, load /kernel:orchestration. If any domain detected (API, auth, frontend, backend): load domain skills. </on_start>
task: what user wants (one sentence) type: bug|feature|refactor|question|verify|resume|review familiar: yes|noSearch before asking: Glob, Grep, common paths.
<ask_user> Use AskUserQuestion when: classification is ambiguous (could be bug or feature, refactor or rewrite) Ask: "This looks like {type_A} but could be {type_B}. Which framing fits your intent?" Options: type_A, type_B, or clarify </ask_user>
After classify: load matching workflow from workflows/{type}.md if it exists. Workflow steps guide the phase sequence. Human confirms at each step (ingest mode).
IF type == resume (or a manifest path was supplied) → go to MANIFEST RESUME (below) IF familiar AND tier_likely_1 → skip to step 3 (scope), mark research="skipped (familiar)" IF unfamiliar OR complex → proceed to step 2 (research) ALWAYS: check _meta/research/ cache regardless (cache != full research) Resume from a kernel.handoff/v1 or kernel.checkpoint/v1 manifest. The runtime CLI: `KM="${CLAUDE_PLUGIN_ROOT:-.}/orchestration/manifest/kernel-manifest"`Discover: explicit path if the user gave one, else:
"$KM" latest # newest across _meta/checkpoints/ + _meta/handoffs/
Legacy markdown handoffs (_meta/handoffs/*.md) remain readable this release: parse goal/decisions/next-steps from prose, note "legacy handoff (deprecated, no validation/divergence/budget)" and suggest regenerating as JSON. Removal path: docs/MIGRATION-8.md.
Validate — a manifest that does not validate is not resumed:
"$KM" validate <manifest> # exit 2 (no parser) on a sealed manifest = STOP
Divergence — live state wins over manifest claims:
"$KM" divergence <manifest> --json
Typed divergence events apply workflow.invalidation_rules[].when and return
recalculated phase statuses. Never trust an inherited phase whose inputs changed.
Preflight: run "$KM" preflight <manifest>. Canonical state permits only typed
current-branch, path-exists, and allowlisted argv checks; raw shell is invalid.
Compile bounded context — read the bundle, not the raw tree:
"$KM" compile <manifest> --bundle-out /tmp/resume-bundle.md --receipt-out _meta/reports/receipt-{date}.json
The receipt (kernel.context-receipt/v1) reports estimated tokens per layer and status: within_budget → proceed · target_exceeded → drop optional selectors, proceed with a note · maximum_exceeded (exit 3) → STOP, report the receipt, ask before loading anything.
Activate the policy (arms the guard-context hook for sealed/bounded):
"$KM" activate <manifest>
sealed: forbidden globs are hook-BLOCKED; do not fight the hook — amend the manifest if access is genuinely needed. bounded: extra loads are allowed but ledgered; justify each in the receipt's loads_beyond_manifest.
Resume at the declared position:
"$KM" resume <manifest> # entry_phase / entrypoint / next_operation
Skip inherited phases (already verified by divergence), execute required ones. Honor execution.stop_conditions and emit checkpoints at execution.checkpoints.
Complete: when outputs.required are verified,
"$KM" deactivate --receipt _meta/reports/receipt-{date}.json
Deactivate projects the receipt into AgentDB's observational context graph (shadow
telemetry). Then outputs.completion (usually agentdb write-end), which records session
outcome on that graph row when did/blocked are present.
Optional advisory (never auto-loads):
bash agentdb graph-suggest {task_type}
Output: "Resuming {manifest}: {goal}. Entry: {entry_phase}. Receipt: {total_estimated_tokens} tokens ({status})."
**RULE: Research without verification is theory fiction.** Every research finding must be verified with a minimal test, prototype, or proof before it drives implementation. 8 research agents and 6 docs mean nothing if nobody built a test to prove the approach works. (LRN-F11) 1. Check existing: ls _meta/research/, agentdb query 2. anti_patterns FIRST: "{tech} not working", "{tech} gotchas" 3. Solutions: official docs, GitHub issues, Stack Overflow 4. Built-in check: framework > stdlib > npm package 5. **Verify**: build minimal proof (test screen, script, unit test) before committing to approach 6. Write to: _meta/research/{topic}.md (include verification result) # {Topic} Research ## Anti-Patterns 1. {pattern}: {why} → {fix} ## Proven Solution - package: {name}@{version} ## Sources - {urls}tier 2+: spawn kernel:researcher
<ask_user> Use AskUserQuestion when: research reveals multiple viable approaches or unknown risks Ask: "Research found {N} approaches. Proceed with {recommended}, or explore alternatives?" Options: proceed, explore alternatives, skip research </ask_user>
files: 1: {path} - {what changes} count: N tier: 1|2|3 1: reversible + loud if wrong → execute inline 2: persistent or moderately quiet → plan, execute inline; delegate a surgeon only for heavy file-disjoint work; verify 3: hard to undo, quiet if wrong, or wide blast radius → contract + surgeon + adversary ambiguous: assume higher. File count is only a weak hint, never the trigger.<ask_user> Use AskUserQuestion when: tier classification is borderline (e.g., 2-3 files but complex coupling) Ask: "Scoped to {N} files — tier {X}. Confirm tier, or should I treat as tier {X+1}?" Options: confirm tier {X}, bump to tier {X+1} </ask_user>
IF scope reveals unknowns not covered by research → loop to step 2 with narrowed query IF scope is clear → proceed to step 4 Define success before coding. Tests first. skill_ref: skills/testing/SKILL.mddone_when:
evals: code_grader: PASS/FAIL command regression: existing tests pass
mock_boundaries_only: external APIs, DBs edge_cases_first: null, empty, boundary, timeout strong_assertions: specific values Spec framing > contract framing. Execution-ready, not goal-shaped.Specification prompts with exact code achieve 100% success across all scopes (modelmind H002/H003, 0.95 confidence). Contract framing ("achieve X under constraint Y") leaves interpretation gaps that agents fill incorrectly.
Before handing to surgeon (tier 2+) or starting execution (tier 1), the spec must answer:
Litmus test: could a fresh agent in a new session execute this spec with zero follow-up questions? If no, the spec is incomplete. Return to step 3 (scope) or step 4 (tests) and fill the gap before proceeding.
Anti-pattern: shipping a contract that says "the surgeon will figure out X." The surgeon will figure out X by guessing, and the guess will be wrong.
<ask_user> Use AskUserQuestion when: the spec has a known gap and you need the user to decide which exact path to take (rather than letting the surgeon guess). Ask: "Spec gap at {location}: option A = {exact}, option B = {exact}. Which?" Options: option A, option B, other </ask_user>
1. Reference research doc 2. Write failing tests (edge cases!) 3. Implement proven pattern 4. Check Big 5: skills/quality/SKILL.md 5. Run evals → /kernel:validate before commit 6. Commit when done_when satisfied<tier_2_plus> rule: you do NOT write code
agentdb learn pattern "{what worked}" "{evidence}" agentdb learn failure "{what broke}" "{evidence}" Update _meta/research/ if new findings. Suggest /kernel:retrospective if 5+ learnings accumulated since last synthesis. Long task still running? Emit /kernel:checkpoint at natural boundaries instead of letting context accumulate (EXP-L21).
agentdb write-end '{"task":"X","tier":N,"learned":["Z"]}' MUST run before session ends.<output_format> task: one sentence | type: bug|feature|refactor | tier: 1|2|3 | status: researching|scoping|testing|executing|complete </output_format>
<hard_stops> ask_file_location→search | code_without_research→step2 | code_without_tests→step4 | code_tier2+→surgeon | skip_agentdb→go_back </hard_stops>
npx claudepluginhub ariaxhan/kernel-claude --plugin kernelMandatory workflow router invoked before any code edits, debugging, planning, or review. Runs entry sequence including token efficiency and routes to the correct skill for the task.
Auto-loop execution workflow with quality gates. Use when starting any non-trivial implementation task. Provides automatic task decomposition, code implementation, testing (L1-L4), and iterative quality gates until completion. Invoke with /autoworker.
Orchestrates all code-modifying development tasks like bug fixes, enhancements, and new features using adaptive phases for analysis, specs, TDD, implementation, and verification.