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Task relationship analysis

Skill jajupmochi/agent-harness/skills/task-relationship-analysis

Use BEFORE executing any multi-step or multi-feature request (3+ tasks). Forces a pre-execution pass that maps how the tasks relate — synergies, conflicts, shared substrate, ordering — so you don't mechanically execute them in listed order and miss that several should be built on one shared piece, or that two conflict. Scaffolds a pairwise matrix + synthesis checklist.From its SKILL.md

Install
npx -y skills add jajupmochi/agent-harness --skill task-relationship-analysis

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

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SKILL.md

2.3 KB, 464 tokens by cl100k_base, as published. Nobody here has run it

task-relationship-analysis

Overhaul task 15. Some agents/models execute a numbered task list mechanically, in order, and miss the cross-task picture — e.g. three separate "add a sub-agent" asks that should be one framework, or two tasks that conflict if done independently. This skill makes the relationship analysis a required first step.

When

Any request with 3+ tasks, or multiple logically separable features, before you start executing.

Do this first

  1. List the tasks, then scaffold the analysis: 
    python3 scripts/scaffold.py "task A" "task B" "task C" …      # or pipe one per line on stdin
    It emits every unordered pair exactly once (nothing skipped) + a synthesis checklist.
  2. Fill each pair with one relationship: SYN (synergy / share substrate) · CONF (conflict) · SEQ (ordering dependency) · INDEP (independent).
  3. Answer the checklist: shared substrate to unify · conflicts to resolve in design · mergeable work · ordering/DAG from the SEQ pairs · cross-cutting constraints to do first.
  4. Only THEN execute — in the order the DAG implies, unifying what the matrix flagged.

Why deterministic scaffold + LLM analysis

scaffold.py is pure code: it guarantees the shape and that every pair is considered. The model does the actual judgement (which pair is SYN vs CONF). LLM-as-component, not the core.

Example payoff (this repo's own overhaul)

The 16-point overhaul's matrix surfaced that tasks 2/3/10a (three "sub-agent" asks) were the SAME framework, and tasks 3/4/5 were ONE memory subsystem — recorded in docs/strategy/…/00-program-plan.md §3 before any code. That is the analysis this skill scaffolds.

Status: v0.1 (pairwise matrix + checklist), tested (test_scaffold.py, 6/6). Planned: auto-ingest a task list from a plan file; a graph export of the SEQ edges.

What ships with it: 2 files

4.9 KB alongside SKILL.md, 2 of them executable

scripts/

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