chore: sync .cursor from suite
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Made-with: Cursor
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Oleksandr Bezdieniezhnykh
2026-04-25 19:44:40 +03:00
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---
name: implement
description: |
Orchestrate task implementation with dependency-aware batching, parallel subagents, and integrated code review.
Implement tasks sequentially with dependency-aware batching and integrated code review.
Reads flat task files and _dependencies_table.md from TASKS_DIR, computes execution batches via topological sort,
launches up to 4 implementer subagents in parallel, runs code-review skill after each batch, and loops until done.
implements tasks one at a time in dependency order, runs code-review skill after each batch, and loops until done.
Use after /decompose has produced task files.
Trigger phrases:
- "implement", "start implementation", "implement tasks"
- "run implementers", "execute tasks"
- "execute tasks"
category: build
tags: [implementation, orchestration, batching, parallel, code-review]
tags: [implementation, batching, code-review]
disable-model-invocation: true
---
# Implementation Orchestrator
# Implementation Runner
Orchestrate the implementation of all tasks produced by the `/decompose` skill. This skill is a **pure orchestrator** — it does NOT write implementation code itself. It reads task specs, computes execution order, delegates to `implementer` subagents, validates results via the `/code-review` skill, and escalates issues.
Implement all tasks produced by the `/decompose` skill. This skill reads task specs, computes execution order, writes the code and tests for each task **sequentially** (no subagents, no parallel execution), validates results via the `/code-review` skill, and escalates issues.
The `implementer` agent is the specialist that writes all the code — it receives a task spec, analyzes the codebase, implements the feature, writes tests, and verifies acceptance criteria.
For each task the main agent receives a task spec, analyzes the codebase, implements the feature, writes tests, and verifies acceptance criteria — then moves on to the next task.
## Core Principles
- **Orchestrate, don't implement**: this skill delegates all coding to `implementer` subagents
- **Dependency-aware batching**: tasks run only when all their dependencies are satisfied
- **Max 4 parallel agents**: never launch more than 4 implementer subagents simultaneously
- **File isolation**: no two parallel agents may write to the same file
- **Sequential execution**: implement one task at a time. Do NOT spawn subagents and do NOT run tasks in parallel. (See `.cursor/rules/no-subagents.mdc`.)
- **Dependency-aware ordering**: tasks run only when all their dependencies are satisfied
- **Batching for review, not parallelism**: tasks are grouped into batches so `/code-review` and commits operate on a coherent unit of work — all tasks inside a batch are still implemented one after the other
- **Integrated review**: `/code-review` skill runs automatically after each batch
- **Auto-start**: batches launch immediately — no user confirmation before a batch
- **Auto-start**: batches start immediately — no user confirmation before a batch
- **Gate on failure**: user confirmation is required only when code review returns FAIL
- **Commit per batch**: after each batch is confirmed, commit. Ask the user whether to push to remote unless the user previously opted into auto-push for this session.
@@ -56,7 +55,7 @@ TASKS_DIR/
- A) Commit or stash stray changes manually, then re-invoke `/implement`
- B) Agent commits stray changes as a single `chore: WIP pre-implement` commit and proceeds
- C) Abort
- Rationale: implementer subagents edit files in parallel and commit per batch. Unrelated uncommitted changes get silently folded into batch commits otherwise.
- Rationale: each batch ends with a commit. Unrelated uncommitted changes would get silently folded into batch commits otherwise.
- This check is repeated at the start of each batch iteration (see step 6 / step 14 Loop).
## Algorithm
@@ -78,8 +77,8 @@ TASKS_DIR/
- Topological sort remaining tasks
- Select tasks whose dependencies are ALL satisfied (completed)
- If a ready task depends on any task currently being worked on in this batch, it must wait for the next batch
- Cap the batch at 4 parallel agents
- A batch is simply a coherent group of tasks for review + commit. Within the batch, tasks are implemented sequentially in topological order.
- Cap the batch size at a reasonable review scope (default: 4 tasks)
- If the batch would exceed 20 total complexity points, suggest splitting and let the user decide
### 4. Assign File Ownership
@@ -89,11 +88,12 @@ The authoritative file-ownership map is `_docs/02_document/module-layout.md` (pr
For each task in the batch:
- Read the task spec's **Component** field.
- Look up the component in `_docs/02_document/module-layout.md` → Per-Component Mapping.
- Set **OWNED** = the component's `Owns` glob (exclusive write for the duration of the batch).
- Set **OWNED** = the component's `Owns` glob (the files this task is allowed to write).
- Set **READ-ONLY** = Public API files of every component in the component's `Imports from` list, plus all `shared/*` Public API files.
- Set **FORBIDDEN** = every other component's `Owns` glob, and every other component's internal (non-Public API) files.
- If the task is a shared / cross-cutting task (lives under `shared/*`), OWNED = that shared directory; READ-ONLY = nothing; FORBIDDEN = every component directory.
- If two tasks in the same batch map to the same component or overlapping `Owns` globs, schedule them sequentially instead of in parallel.
Since execution is sequential, there is no parallel-write conflict to resolve; ownership here is a **scope discipline** check — it stops a task from drifting into unrelated components even when alone.
If `_docs/02_document/module-layout.md` is missing or the component is not found:
- STOP the batch.
@@ -102,31 +102,30 @@ If `_docs/02_document/module-layout.md` is missing or the component is not found
### 5. Update Tracker Status → In Progress
For each task in the batch, transition its ticket status to **In Progress** via the configured work item tracker (see `protocols.md` for tracker detection) before launching the implementer. If `tracker: local`, skip this step.
For each task in the batch, transition its ticket status to **In Progress** via the configured work item tracker (see `protocols.md` for tracker detection) before starting work. If `tracker: local`, skip this step.
### 6. Launch Implementer Subagents
### 6. Implement Tasks Sequentially
**Per-batch dirty-tree re-check**: before launching subagents, run `git status --porcelain`. On the first batch this is guaranteed clean by the prerequisite check. On subsequent batches, the previous batch ended with a commit so the tree should still be clean. If the tree is dirty at this point, STOP and surface the dirty files to the user using the same A/B/C choice as the prerequisite check. The most likely causes are a failed commit in the previous batch, a user who edited files mid-loop, or a pre-commit hook that re-wrote files and was not captured.
**Per-batch dirty-tree re-check**: before starting the batch, run `git status --porcelain`. On the first batch this is guaranteed clean by the prerequisite check. On subsequent batches, the previous batch ended with a commit so the tree should still be clean. If the tree is dirty at this point, STOP and surface the dirty files to the user using the same A/B/C choice as the prerequisite check. The most likely causes are a failed commit in the previous batch, a user who edited files mid-loop, or a pre-commit hook that re-wrote files and was not captured.
For each task in the batch, launch an `implementer` subagent with:
- Path to the task spec file
- List of files OWNED (exclusive write access)
- List of files READ-ONLY
- List of files FORBIDDEN
- **Explicit instruction**: the implementer must write or update tests that validate each acceptance criterion in the task spec. If a test cannot run in the current environment (e.g., TensorRT requires GPU), the test must still be written and skip with a clear reason.
For each task in the batch **in topological order, one at a time**:
1. Read the task spec file.
2. Respect the file-ownership envelope computed in Step 4 (OWNED / READ-ONLY / FORBIDDEN).
3. Implement the feature and write/update tests for every acceptance criterion in the spec. If a test cannot run in the current environment (e.g., TensorRT requires GPU), the test must still be written and skip with a clear reason.
4. Run the relevant tests locally before moving on to the next task in the batch. If tests fail, fix in-place — do not defer.
5. Capture a short per-task status line (files changed, tests pass/fail, any blockers) for the batch report.
Launch all subagents immediately — no user confirmation.
Do NOT spawn subagents and do NOT attempt to implement two tasks simultaneously, even if they touch disjoint files. See `.cursor/rules/no-subagents.mdc`.
### 7. Monitor
### 7. Collect Status
- Wait for all subagents to complete
- Collect structured status reports from each implementer
- If any implementer reports "Blocked", log the blocker and continue with others
- After all tasks in the batch are finished, aggregate the per-task status lines into a structured batch status.
- If any task reported "Blocked", log the blocker with the failing task's ID and continue — the batch report will surface it.
**Stuck detection** — while monitoring, watch for these signals per subagent:
- Same file modified 3+ times without test pass rate improving → flag as stuck, stop the subagent, report as Blocked
- Subagent has not produced new output for an extended period → flag as potentially hung
- If a subagent is flagged as stuck, do NOT let it continue looping — stop it and record the blocker in the batch report
**Stuck detection** — while implementing a task, watch for these signals in your own progress:
- The same file has been rewritten 3+ times without tests going green → stop, mark the task Blocked, and move to the next task in the batch (the user will be asked at the end of the batch).
- You have tried 3+ distinct approaches without evidence-driven progress → stop, mark Blocked, move on.
- Do NOT loop indefinitely on a single task. Record the blocker and proceed.
### 8. AC Test Coverage Verification
@@ -139,8 +138,8 @@ Before code review, verify that every acceptance criterion in each task spec has
- **Not covered**: no test exists for this AC
If any AC is **Not covered**:
- This is a **BLOCKING** failure — the implementer must write the missing test before proceeding
- Re-launch the implementer with the specific ACs that need tests
- This is a **BLOCKING** failure — the missing test must be written before proceeding
- Go back to the offending task, add tests for the specific ACs that lack coverage, then re-run this check
- If the test cannot run in the current environment (GPU required, platform-specific, external service), the test must still exist and skip with `pytest.mark.skipif` or `pytest.skip()` explaining the prerequisite
- A skipped test counts as **Covered** — the test exists and will run when the environment allows
@@ -264,9 +263,9 @@ After each batch, produce a structured report:
| Situation | Action |
|-----------|--------|
| Implementer fails same approach 3+ times | Stop it, escalate to user |
| Same task rewritten 3+ times without green tests | Mark Blocked, continue batch, escalate at batch end |
| Task blocked on external dependency (not in task list) | Report and skip |
| File ownership conflict unresolvable | ASK user |
| File ownership violated (task wrote outside OWNED) | ASK user |
| Test failure after final test run | Delegate to test-run skill — blocking gate |
| All tasks complete | Report final summary, suggest final commit |
| `_dependencies_table.md` missing | STOP — run `/decompose` first |
@@ -281,7 +280,7 @@ Each batch commit serves as a rollback checkpoint. If recovery is needed:
## Safety Rules
- Never launch tasks whose dependencies are not yet completed
- Never allow two parallel agents to write to the same file
- If a subagent fails or is flagged as stuck, stop it and report — do not let it loop indefinitely
- Never start a task whose dependencies are not yet completed
- Never run tasks in parallel and never spawn subagents — see `.cursor/rules/no-subagents.mdc`
- If a task is flagged as stuck, stop working on it and report — do not let it loop indefinitely
- Always run the full test suite after all batches complete (step 15)
@@ -3,29 +3,31 @@
## Topological Sort with Batch Grouping
The `/implement` skill uses a topological sort to determine execution order,
then groups tasks into batches for parallel execution.
then groups tasks into batches for code review and commit. Execution within a
batch is **sequential** — see `.cursor/rules/no-subagents.mdc`.
## Algorithm
1. Build adjacency list from `_dependencies_table.md`
2. Compute in-degree for each task node
3. Initialize batch 0 with all nodes that have in-degree 0
3. Initialize the ready set with all nodes that have in-degree 0
4. For each batch:
a. Select up to 4 tasks from the ready set
b. Check file ownership — if two tasks would write the same file, defer one to the next batch
c. Launch selected tasks as parallel implementer subagents
d. When all complete, remove them from the graph and decrement in-degrees of dependents
e. Add newly zero-in-degree nodes to the next batch's ready set
a. Select up to 4 tasks from the ready set (default batch size cap)
b. Implement the selected tasks one at a time in topological order
c. When all tasks in the batch complete, remove them from the graph and
decrement in-degrees of dependents
d. Add newly zero-in-degree nodes to the ready set
5. Repeat until the graph is empty
## File Ownership Conflict Resolution
## Ordering Inside a Batch
When two tasks in the same batch map to overlapping files:
- Prefer to run the lower-numbered task first (it's more foundational)
- Defer the higher-numbered task to the next batch
- If both have equal priority, ask the user
Tasks inside a batch are executed in topological order — a task is only
started after every task it depends on (inside the batch or in a previous
batch) is done. When two tasks have the same topological rank, prefer the
lower-numbered (more foundational) task first.
## Complexity Budget
Each batch should not exceed 20 total complexity points.
If it does, split the batch and let the user choose which tasks to include.
The budget exists to keep the per-batch code review scope reviewable.