Agent skill
helix-meta-planner
Insight-driven planning. Recalls memory, explores informed by insights, decomposes via planner, writes plan.
Install this agent skill to your Project
npx add-skill https://github.com/enzokro/crinzo-plugins/tree/main/helix/skills/helix-meta-planner
SKILL.md
Meta-Planner
Plan-mode-only skill. Produces an implementation plan informed by helix's accumulated project insights.
Environment
HELIX="$(cat .helix/plugin_root)"
Phases: RECALL → EXPLORE → PLAN → SYNTHESIZE → EXIT
1. RECALL
python3 "$HELIX/lib/injection.py" strategic-recall "$ARGUMENTS"
Parse JSON. Use summary for triage, synthesize insights into blocks:
- CONSTRAINTS — proven insights (
_effectiveness >= 0.70): decomposition rules, verification needs, sequencing. - RISK_AREAS — risky insights (
_effectiveness < 0.40) orderived/failuretags: flag for extra verification, smaller tasks. - EXPLORATION_TARGETS — areas referenced by insights that expand scope beyond the naive objective.
- GRAPH_DISCOVERED —
_hop: 1insights (graph-adjacent, not direct match). Treat as exploration targets.
Triage signals: coverage_ratio > 0.3 = well-mapped, trust constraints. < 0.1 = uncharted, expand exploration. graph_expanded_count > 0 = graph surfacing related context.
If recall returns empty -- proceed without constraints; first sessions have no memory.
2. EXPLORE
Map areas relevant to both objective and insight-identified targets.
git ls-files | head -80-- identify 3-6 natural partitions.- Select partitions: union of (a) obviously relevant to objective and (b) areas flagged by RECALL insights.
- Spawn explorer swarm:
subagent_type="helix:helix-explorer",model=sonnet,max_turns=30. All in ONE message. Prompt:SCOPE: {partition}\nFOCUS: {focus}\nOBJECTIVE: $ARGUMENTS. - Merge findings by file path. Proceed with successful explorers on error.
Obvious scope (single module, clear file set): skip swarm, use Glob/Grep/Read directly.
3. PLAN
Spawn planner: subagent_type="helix:helix-planner", max_turns=500. Prompt: OBJECTIVE: $ARGUMENTS\nEXPLORATION: {merged_findings_json}\nCONSTRAINTS: {constraints_from_recall}\nRISK_AREAS: {risk_areas_from_recall}. Omit empty blocks. Parse PLAN_SPEC JSON array.
If decomposition raises questions -- use AskUserQuestion to resolve before synthesis.
4. SYNTHESIZE
Write the plan file (path from system context):
# {Objective summary}
## Context
Why this change is needed — the problem, what prompted it, intended outcome.
## Insights Applied
Relevant helix insights and how each shaped the plan:
- [eff%] insight content → influenced {which decision}
## Key Files
Files identified by exploration, grouped by concern:
- {area}: `file1.py`, `file2.py` — {what they do, why they matter}
## Implementation Plan
### 1. {slug} (seq)
{description}
- **Files:** relevant_files
- **Depends on:** blocked_by (or "none — parallel")
- **Verify:** command
### 2. {slug} (seq)
...
## Verification
How to test the complete change end-to-end.
Quality bar: A developer reading the plan should know exactly what changes, in what order, verified how — without re-exploring the codebase.
5. EXIT
Call ExitPlanMode to present the plan for user approval.
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