| name | anti-legacy:orchestrate |
| description | Master orchestrator for the anti-legacy pipeline. Sequences all 16 phases (plus an optional semantic-join phase for multi-repo surveys), enforces all eight gates (GATE_0_DISCOVERY, GATE_1_DESIGN, GATE_1B_SEMANTIC_JOIN, GATE_2_PLAN, GATE_3_BUILD, GATE_3B_SEMANTIC, GATE_4_UAT, GATE_5_COMPLETENESS), and resumes from wherever it left off. Start here โ this skill dispatches everything else. |
Orchestrate โ Pipeline Runner
Master entry point for the anti-legacy modernization pipeline. Sequences all
phases, enforces gates, and resumes from the current manifest state.
There are eight gates total, matching anti-legacy:gatekeeper's enumeration:
GATE_0_DISCOVERY (automated, after survey), GATE_1_DESIGN, GATE_1B_SEMANTIC_JOIN
(only for multi-repo semantic-join surveys), GATE_2_PLAN, GATE_3_BUILD (automated),
GATE_3B_SEMANTIC, GATE_4_UAT, and GATE_5_COMPLETENESS (automated, final completeness
gate). Four of these (GATE_1_DESIGN, GATE_2_PLAN, GATE_3B_SEMANTIC, GATE_4_UAT)
require human sign-off; the rest are automated. Every --opinion passed sign-off MUST cite
--evidence with registered artifact ids โ the manifest content-verifies each cited id
(registered AND status not failed/pending AND file present AND checksum matches) and
hard-fails the gate otherwise.
Generalized gate kick-back. Recording any gate --opinion failed rewinds the pipeline
to that gate's producing phase (a guided reset โ manifest.py resets phase.current,
names the skill to re-run, and exits non-zero / code 3). It does NOT auto-dispatch the
skill. On a non-zero manifest gate exit, read the printed reset target and re-run the
named producing skill before re-presenting the gate. See anti-legacy:gatekeeper
(Generalized gate kick-back) for the full per-gate phase/skill map.
Three phases host the content agents' work between gates: functional-tests (after
GATE_2_PLAN, before swarm โ blocking pre-build validation), document (after GATE_4_UAT,
before final-review โ the documentation pass), and final-review (after document, before
deploy โ the automated GATE_5_COMPLETENESS completeness gate). Their producing skills are
dispatched in the phase table below; this skill only sequences them.
How to Invoke
"Run the anti-legacy pipeline" or "Continue the modernization"
Prerequisites
- Legacy source code accessible as a local directory
python3 availablegit initialized in the workspace
Workflow
Step 1 โ Read Pipeline State
python3 .anti-legacy/run.py manifest status
If manifest doesn't exist, start from Phase 1 (setup). Otherwise, resume from
the current phase reported by status.
Step 2 โ Execute the Current Phase
Use the phase dispatch table below. After each phase completes, check if a gate
blocks the next phase. After each phase, run python3 .anti-legacy/run.py manifest status to confirm advancement.
Phase Dispatch Table
Execute phases in order. Each phase produces one primary artifact.
After each phase, run python3 .anti-legacy/run.py manifest status to confirm advancement.
Phase 1: Setup
Skill: anti-legacy:setup
Produces: .anti-legacy/manifest.json, config.json
Blocks: Nothing โ always runs first
Gate: None
What to do:
1. Run anti-legacy:setup to initialize the workspace
2. Confirm manifest.json exists and shows phase: survey
3. If the user hasn't specified a target stack, ask now
Phase 2: Survey
Skill: anti-legacy:survey
Produces: per-app .anti-legacy/graphs/<app>.db + .anti-legacy/legacy-graph.digest.txt
Blocks: Must have config.json with legacy source paths
Gate: None
What to do:
1. Run anti-legacy:survey, which shells `wicked-estate index <path> --db .anti-legacy/graphs/<app>.db`
(via the `wicked_estate` helper) once per `source_apps` entry โ one DB per source repo so
cross-graph federation (the multi-repo merge case) works. Handles mainframe (COBOL, JCL, CICS,
IMS, DB2) and modern (Java/.NET/Python) sources alike โ wicked-estate owns indexing.
2. Validate: each per-app DB has โฅ1 behavior-bearing node (`wicked-estate stats` reports node/edge counts).
3. Re-project confirmed domain terms onto each fresh DB: python3 .anti-legacy/run.py vocabulary project --db .anti-legacy/graphs/<app>.db
โ a `--fresh` index WIPES prior `domain_*` term tags (they live only in the gitignored DB), so re-apply them.
No-op on the first survey (nothing confirmed yet); MANDATORY on any re-survey after extraction confirmed terms.
4. Write the deterministic stats digest: python3 .anti-legacy/run.py wicked_estate write_digest --out .anti-legacy/legacy-graph.digest.txt --db .anti-legacy/graphs/<app>.db [--db ... per app]
5. Register the digest (text, no --schema): python3 .anti-legacy/run.py manifest register legacy-graph --path legacy-graph.digest.txt --format text --produced-by anti-legacy:survey --status final
6. Advance: python3 .anti-legacy/run.py manifest advance survey
Cross-phase invariant โ reproject after every graph rebuild. Domain-term tags
(domain_*) are a disposable projection of the committed glossary onto the gitignored,
rebuilt-by-survey graph DB โ never the system of record. Any phase that rebuilds a graph
(a fresh survey) or confirms new terms (extraction) MUST re-run vocabulary project, or
the engine's cluster/by-requirement/read-kv silently degrade to name-only
resolution. See anti-legacy:vocabulary (Project confirmed terms) for the two-axes model.
Phase 3: Analyze
Skill: anti-legacy:analyze
Produces: analysis.md (complexity, risk, shared assets)
Blocks: Must have legacy-graph registered (the survey digest + per-app DBs under .anti-legacy/graphs/)
Gate: None
What to do:
1. Run anti-legacy:analyze โ it queries the per-app graphs via the `wicked_estate` helper
(`python3 .anti-legacy/run.py wicked_estate <cmd> --db .anti-legacy/graphs/<app>.db`):
entry points + importance via `rank` (PageRank), shared-asset coupling via cross-domain
`blast_radius` (estate uses/accesses edges), batch-vs-online via JCL/CICS estate node kinds.
Multi-repo coupling uses `cross_graph` over the per-app DB list.
2. Surface shared tables/files, complexity metrics, risk areas โ every claim traced to a helper query.
3. Register and advance
Phase 4: Extraction (crawl โ annotate โ coverage)
Skill: anti-legacy:extraction
Produces: .anti-legacy/coverage-report.json + .anti-legacy/coverage-report.md,
the .anti-legacy/annotations.jsonl IP overlay, and written wicked-estate requirement fields
Blocks: Must have legacy-graph registered (survey digest + per-app DBs) and analysis.md
Gate: None โ but feeds GATE_1
Phase value: advances graph-translate
What to do:
1. Run anti-legacy:extraction. It crawls the per-app graph with adaptive ring expansion
(node + 1 up / 1 down via the `wicked_estate` helper's blast_radius/query/source), driving
the worklist most-important-first off `wicked-estate rank`.
2. Per behavior-bearing node, the skill ends RESOLVED (rule + confidence/provenance written via
`we.annotate` into the wicked-estate `requirement` field AND mirrored to
`.anti-legacy/annotations.jsonl`) or RISK-flagged (placed on the HITL research queue). No
bare nodes โ every behavior-bearing node terminates RESOLVED or RISK.
3. Emit coverage: python3 .anti-legacy/run.py coverage --db .anti-legacy/graphs/<app>.db --out .anti-legacy/coverage-report.json
(resolved-or-flagged metric over behavior-bearing nodes; exits non-zero while coverage < 1.0).
4. Done-gate (BLOCKING): do not register/advance until coverage.py exits 0 (coverage == 1.0,
UNACCOUNTED == 0) โ the provable terminal of ยงI2. The printed unaccounted SymbolIds are the
remaining worklist.
5. Register coverage evidence: python3 .anti-legacy/run.py manifest register coverage-report --path coverage-report.json --format json --produced-by anti-legacy:extraction --status final --depends-on legacy-graph
6. Project confirmed domain terms onto the graph (extraction is where terms reach `confirmed`):
python3 .anti-legacy/run.py vocabulary project --db .anti-legacy/graphs/<app>.db
โ binds confirmed terms as native `domain_*` tags so the domain graph / clustering resolves
through the engine. Read the summary: a `GAP:` line (`unbound` / `all_skipped`) is a coverage
signal to note in the status report, not a blocker. `confirmed_available=0` is a clean no-op.
A `DRIFT:` line (same glossary, changed binding set) is a re-review trigger (ISS-04).
6b. Reprojection-enforcement gate (BLOCKING โ ISS-03): do not advance until the projection is
present. A fresh survey wipes domain_* tags, so this catches a skipped reproject:
python3 .anti-legacy/run.py vocabulary check-projection --db .anti-legacy/graphs/<app>.db
โ exit 1 (BLOCKED) iff confirmed terms ground on the graph but it carries 0 domain_* tags;
exit 0 when there is nothing to enforce (no confirmed terms, or none present in this graph).
7. Refresh + re-register the digest so it reflects the freshly written `requirement` fields:
python3 .anti-legacy/run.py wicked_estate write_digest --out .anti-legacy/legacy-graph.digest.txt --db .anti-legacy/graphs/<app>.db [--db ...]
then python3 .anti-legacy/run.py manifest register legacy-graph --path legacy-graph.digest.txt --format text --produced-by anti-legacy:extraction --status final
8. Advance: python3 .anti-legacy/run.py manifest advance graph-translate
Phase 4b: Graph Translator (re-think โ domain graph)
Skill: anti-legacy:graph-translator
Produces: .anti-legacy/requirements/requirements_graph.json, .anti-legacy/requirements/dispositions.json,
.anti-legacy/requirements/roundtrip-coverage.json
Blocks: Must have completed extraction (coverage == 1.0)
Gate: None
Phase value: remains in graph-translate (same manifest phase slot as extraction)
What to do:
1. Run anti-legacy:graph-translator. It consumes the ANNOTATED code graph
(wicked-estate DBs with requirement fields + annotations.jsonl overlay)
plus the cluster communities (wicked-estate cluster weight=calls) and
re-thinks them into the TARGET-STATE domain graph.
2. Disposition per legacy rule: keep | modify | drop | new.
Every `drop` requires explicit rationale (written to dispositions.json).
3. Requirement-coverage invariant: the domain graph must cover EVERY
requirement edge from the annotated code graph. 0 silent drops.
python3 .anti-legacy/run.py domain_graph --db .anti-legacy/graphs/<app>.db --out .anti-legacy/requirements/requirements_graph.json
4. Register: python3 .anti-legacy/run.py manifest register requirements-graph --path requirements/requirements_graph.json --format json --schema schemas/requirements-graph.enriched.schema.json --produced-by anti-legacy:graph-translator --status final --depends-on legacy-graph,coverage-report
5. Register the disposition-aware round-trip evidence (the checksummed audit seam GATE_1_DESIGN cites โ proves every legacy rule is represented OR dropped-with-reason): python3 .anti-legacy/run.py manifest register roundtrip-coverage --path requirements/roundtrip-coverage.json --format json --produced-by anti-legacy:graph-translator --status final --depends-on requirements-graph
6. Advance: python3 .anti-legacy/run.py manifest advance blueprint
Phase 5: Blueprint
Skill: anti-legacy:blueprint
Produces: blueprint.json
Blocks: Must have requirements_graph.json
Gate: None
What to do:
1. Read the requirements graph
2. Design target architecture โ packages, services, data layer
3. Map each requirement to target files
4. Register blueprint.json
5. Advance
Phase 6: Test Strategy
Skill: anti-legacy:test-strategy
Produces: contracts/{req_id}.json for each requirement
Blocks: Must have blueprint.json
Gate: None
What to do:
1. For each requirement, generate a test contract
2. Each contract must have โฅ1 happy_path, โฅ1 error scenario
3. Numeric outputs must have parity_rules
4. Register contracts
5. Advance
Phase 7: Review Packet
Skill: anti-legacy:review-packet
Produces: review_packet.md
Blocks: Must have requirements_graph.json + blueprint.json + contracts/
Gate: None โ but feeds GATE_1
What to do:
1. Produce the stakeholder deliverables package first: run `anti-legacy:deliverables`
(PRD, diagrams, test strategy + scripts, migration plan, risk/decisions/evidence logs โ
.anti-legacy/deliverables/). It registers each deliverable; it does NOT advance the phase.
2. Run packet_generator to compile the review packet
3. Print a summary of the packet AND the deliverables package (deliverables/README.md) for the user
4. Register review_packet.md
5. Advance
๐ง GATE 1 โ Design Review
Skill: anti-legacy:gatekeeper
Requires: requirements_graph.json + blueprint.json + contracts/ + review_packet.md
STOP. This gate requires human review and sign-off.
Tell the user:
"The review packet is ready at review_packet.md.
Please review the requirements graph, blueprint, and contracts,
and sign off when ready.
Say 'approve gate 1' to continue."
Do NOT proceed until the user explicitly approves.
When approved: python3 .anti-legacy/run.py manifest gate GATE_1_DESIGN --opinion passed --evaluator <user> --evidence review-packet,requirements-graph,blueprint-json
Phase 8: Planner
Skill: anti-legacy:planner
Produces: task.md (topologically sorted build plan)
Blocks: GATE_1 must be approved (needs blueprint.json + contracts/)
Gate: None โ but feeds GATE_2
What to do:
1. Topologically sort requirements by dependencies
2. Group into layers: L0=entities, L1=repositories, L2=services, L3=API
3. Estimate hours per task
4. Register task.md
5. Advance
๐ง GATE 2 โ Plan Review
Skill: anti-legacy:gatekeeper
Requires: task-plan (task.md) + blueprint.json
STOP. This gate requires human review and sign-off.
Tell the user:
"The execution plan is ready at task.md.
{N} tasks in {L} layers, estimated {H} total hours.
Say 'approve gate 2' to continue."
Do NOT proceed until the user explicitly approves.
When approved: python3 .anti-legacy/run.py manifest gate GATE_2_PLAN --opinion passed --evaluator <user> --evidence task-plan
Phase 8b: Functional Tests (pre-build validation)
Skill: built separately (content agent) โ slotted at the functional-tests phase
Produces: the pre-build functional-test artifacts (owned by that skill)
Blocks: GATE_2 must be approved โ this is a BLOCKING pre-build validation pass
Gate: None โ but it MUST pass before swarm starts building
Phase value: advances functional-tests
What to do:
1. Advance into the functional-tests phase: python3 .anti-legacy/run.py manifest advance functional-tests
2. Run the functional-tests skill (built separately) to validate the approved plan/contracts
against expected behavior BEFORE any target code is written. This is the blocking
pre-build gate-of-discipline: a failure here means the plan is not yet buildable.
3. Do NOT advance to `build` until this phase's done-gate is satisfied.
4. Advance: python3 .anti-legacy/run.py manifest advance build
Phase 9: Swarm Build
Skill: anti-legacy:swarm
Produces: Target source files per task.md
Blocks: GATE_2 must be approved AND functional-tests phase complete
Gate: None
What to do:
1. Read task.md โ execute tasks layer by layer (L0 first)
2. For each task, dispatch a anti-legacy:developer subagent with:
- The requirement from requirements_graph.json
- The target file from blueprint.json
- The test contract from contracts/
- Access to the legacy source via file_path
3. Wait for each layer to complete before starting the next
4. Track completed tasks in task.md (mark [x])
5. Advance when all tasks are done
Phase 10: Target Review
Skill: anti-legacy:target-review
Produces: evidence/build-integrity.json
Blocks: Must have built target files
Gate: GATE_3 (auto-clear)
What to do:
1. Run `python3 .anti-legacy/run.py validator_discovery run --gate GATE_3_BUILD --workspace {target_path} --config .anti-legacy/config.json` (target_verifier.py is removed; validator_discovery.py is the verifier)
2. If build fails, report errors back to the swarm for fixing
3. Loop until build passes
4. Register evidence (`build-integrity`, `code-quality`, `security-scan`, `functional-comparison-report`)
5. Gate auto-clears when `evidence/build-integrity.json` has top-level `status: PASS` AND `evidence/functional_comparison_report.json` reports 0 FAIL with `rule_coverage >= 1.0` (both enforced deterministically by `validator_discovery._run_gate_3_build`)
๐ง GATE 3 โ Build Integrity (Automated)
Auto-clears when evidence/build-integrity.json has top-level status: PASS
AND evidence/functional_comparison_report.json reports 0 FAIL requirements with
rule_coverage >= 1.0. No human intervention needed.
The sign-off MUST cite the registered build evidence โ the manifest content-verifies
each id, so a no-evidence clear hard-fails:
python3 .anti-legacy/run.py manifest gate GATE_3_BUILD --opinion passed --evaluator anti-legacy:target-review --evidence build-integrity,code-quality,security-scan,functional-comparison-report
Phase 11: Semantic Validation
Skill: anti-legacy:semantic-validation
Produces: evidence/semantic-validation-report.json, evidence/semantic_validation_report.md
Blocks: GATE_3 must be approved
Gate: None โ but feeds GATE_3B
What to do:
1. Run `python3 .anti-legacy/run.py semantic_validator` to extract connected dependency chains
2. Deploy @validator subagent to perform side-by-side legacy vs target code review
3. Identify semantic discrepancies and record gaps using `python3 .anti-legacy/run.py semantic_validator record-gap`
4. Update requirements_graph.json to back-propagate the gaps
5. Register evidence and advance
๐ง GATE 3B โ Semantic Review
Skill: anti-legacy:gatekeeper
Requires: semantic-validation-report
STOP. This gate requires human review and sign-off.
Tell the user:
"Semantic validation is complete. {G} gaps identified.
Review evidence/semantic_validation_report.md for details.
Say 'approve gate 3b' to continue."
Do NOT proceed until the user explicitly approves.
When approved: python3 .anti-legacy/run.py manifest gate GATE_3B_SEMANTIC --opinion passed --evaluator <user> --evidence semantic-validation-report
Phase 12: UAT Crew
Skill: anti-legacy:uat-crew
Produces: evidence/uat/{domain}.json per domain
Blocks: GATE_3B must be approved
Gate: None โ but feeds GATE_4
What to do:
1. Dispatch anti-legacy:uat-reviewer subagent (read-only, different from build subagent)
2. Review each requirement's target implementation against:
- Business rules in requirements_graph.json
- Test contracts in contracts/
- Legacy behavior from legacy source
3. Produce verdict per domain: PASS or FAIL
4. FAIL if any CRITICAL or MAJOR finding
5. Register evidence
6. Advance
๐ง GATE 4 โ UAT Review
Skill: anti-legacy:gatekeeper
Requires: All UAT evidence files
STOP. This gate requires human review and sign-off.
Tell the user:
"UAT is complete. {P} domains passed, {F} domains need attention.
Review evidence/uat/ for findings.
Say 'approve gate 4' to continue."
Do NOT proceed until the user explicitly approves.
When approved: python3 .anti-legacy/run.py manifest gate GATE_4_UAT --opinion passed --evaluator <user> --evidence uat-summary,uat-verdicts
Phase 12b: Document
Skill: built separately (content agent) โ slotted at the document phase
Produces: the documentation artifacts (owned by that skill)
Blocks: GATE_4 must be approved
Gate: None โ but feeds GATE_5_COMPLETENESS
Phase value: advances document
What to do:
1. Advance into the document phase: python3 .anti-legacy/run.py manifest advance document
2. Run the document skill (built separately) to produce the target-system documentation
(architecture, runbook, requirement-to-code traceability, etc.).
3. Advance: python3 .anti-legacy/run.py manifest advance final-review
Phase 12c: Final Review (GATE 5 โ Completeness, Automated)
Skill: anti-legacy:gatekeeper (check) + the final-review completeness-report writer (built separately)
Produces: evidence/completeness_report.json (registered as completeness-report)
Blocks: Must be at the final-review phase with document complete
Gate: GATE_5_COMPLETENESS (auto-clear on completeness-report status: PASS; kicks back to document on FAIL)
What to do:
1. Run the final-review completeness check (built separately), which writes
evidence/completeness_report.json and registers it as `completeness-report`.
2. Auto-clear when the report status is PASS:
python3 .anti-legacy/run.py manifest gate GATE_5_COMPLETENESS --opinion passed --evaluator anti-legacy:final-review --evidence completeness-report
3. On FAIL, record failed โ this kicks the pipeline BACK to the `document` phase
(manifest resets phase.current and exits non-zero / code 3); re-run the document
skill, then re-present GATE_5:
python3 .anti-legacy/run.py manifest gate GATE_5_COMPLETENESS --opinion failed --evaluator anti-legacy:final-review --rationale "{reason}"
4. Once GATE_5 is passed/waived, advance to deploy.
๐ง GATE 5 โ Completeness (Automated)
Auto-clears when evidence/completeness_report.json has top-level status: PASS.
A FAIL recorded via --opinion failed kicks the pipeline back to the document phase
(see Generalized gate kick-back, above) โ no full restart. No human intervention needed.
python3 .anti-legacy/run.py manifest gate GATE_5_COMPLETENESS --opinion passed --evaluator anti-legacy:final-review --evidence completeness-report
Phase 13: Deploy
Skill: anti-legacy:deploy
Produces: Deployment artifacts (Dockerfile, CI config, etc.)
Blocks: GATE_5_COMPLETENESS must be passed/waived (leaving final-review requires it)
Gate: None
What to do:
1. Generate deployment configuration for target stack
2. Register artifacts
3. Advance to "complete"
4. Print final summary
Resume Logic
When resuming a pipeline that's already in progress:
- Run
python3 .anti-legacy/run.py manifest status โ read current_phase
- Check if a gate is blocking (PENDING gates before current phase)
- If gate is blocking, tell the user what needs approval
- If no gate blocking, execute the current phase from the dispatch table
- After phase completes, check for the next gate or advance
Error Handling
If any phase fails:
- Do NOT advance the manifest
- Report the specific failure to the user
- The user can say "retry" to re-run the current phase
- The user can say "skip" to manually advance (not recommended)
Completion
When all phases are done and all gates are cleared:
Pipeline complete.
Summary:
- Legacy source: {path}
- Target stack: {stack}
- Requirements: {count}
- Domains: {count}
- Build: PASS
- UAT: {verdict}
- Artifacts: {list}
