agentleFS
LazyIsEfficientLazyIsEfficient/agentic-os/.claude/skills/planning-and-task-breakdown/SKILL.md

planning-and-task-breakdown

Skill17 starsChanged 23 days agoMITView on GitHub

Breaks work into ordered, parallel-dispatchable tasks with an execution DAG. Output format is consumable by CI matrices and parallel agent runners — each task has a stable ID, declared file writes, conflict edges, and branch suffix. Use when you have a spec, brief, or shaper output and need to decompose it into implementable units. Use when a task feels too large, when scope spans multi-repo or multi-week work, or when parallel execution across multiple agents is on the table.

77 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use constraint-driven-development, deprecation-and-migration and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • MrCipherSmithSkill

    constraint-driven-development

    Use when a project needs a persistent, measurable quality bar — starting a project without documented standards, 'set up constraints', or when coverage/perf/a11y thresholds get re-debated per-PR. Produces CONSTRAINTS.md with enforceable numbers, ratchets, and a guard against silent weakening. NOT for throwaway prototypes or a one-off CI setup.

    Also in 14 projects that use this

  • HK-hubSkill

    deprecation-and-migration

    Manages deprecation and migration. Use when removing old systems, APIs, or features. Use when migrating users from one implementation to another. Use when deciding whether to maintain or sunset existing code.

    Also in 34 projects that use this

  • HK-hubSkill

    observability-and-instrumentation

    Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the available data.

    Also in 26 projects that use this

  • seikaikyoSkill

    doubt-driven-development

    對非平凡決策啟動新鮮 context 對抗審查(找碴不背書),在修正還便宜的時候抓出錯誤方向。適用:高風險改動(production、資安敏感邏輯、不可逆操作)、不熟的程式碼、要宣稱「這樣是安全的 / 可行的」之前。機械性操作與一行修改不適用。

    Also in 30 projects that use this

  • seikaikyoSkill

    interview-me

    需求不明時的意圖萃取訪談:一次一題、每題附上自己的猜測、聽出「真正想要 vs 覺得應該要」,直到能預測使用者反應(約 95% 信心)才動工。適用:需求缺少對象 / 動機 / 成功標準 / 約束,或使用者點名「訪談我」「先確認一下」「我們確定嗎」。明確自足的指示、純資訊查詢、機械性操作不適用。

    Also in 31 projects that use this

  • GSA-TTSSkill

    architecture-decision-records

    Load when a user wants architecture decision records (ADRs) drafted from requirements or a design discussion, asks which decisions need an ADR, or wants an ADR draft reviewed for one-sided trade-offs, weak alternatives or missing requirement links. Not for setting up a project's whole documentation system (project-documentation-system).

    Also in 3 projects that use this

  • +2 more from HK-hub

The file

We split this skill into the rules it gives an agent

7 rules. 1 is common, 4 are distinctive, and 2 are very specific to this project.

  • 1

    Common

    Most of the 70 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    After a /shape brief covering multi-repo, multi-week, or multi-slice work

    line 17
  2. Distinctive:

    When a spec or task feels too large to start in one session

    line 18
  3. Distinctive:

    When work needs to parallelize across agents or sessions

    line 19
  4. Distinctive:

    When implementation order isn't obvious

    line 20
  5. Distinctive:

    Plan mode: Read in read-only mode. Map dependencies, note risks.

    line 26
  6. Very specific:

    Stable IDs, never renumbered: Use content-based slugs (T-auth-schema).

    line 35
  7. Common:

    Before starting implementation, confirm:

    line 53

“Common” is measured: kept by at least 6 in 10 of the 70 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Planning and Task Breakdown

Decompose work into small, verifiable tasks with a parallel-dispatchable structure. The output is a plan document — never code — that downstream runners (CI matrices, single-agent execution sessions) consume to do the work.

When to use

  • After a /shape brief covering multi-repo, multi-week, or multi-slice work
  • When a spec or task feels too large to start in one session
  • When work needs to parallelize across agents or sessions
  • When implementation order isn't obvious

When not to use. Single-file changes with obvious scope, or specs that already contain well-defined tasks.

The planning process

  1. Plan mode. Read in read-only mode. Map dependencies, note risks. Do not write code during planning.
  2. Identify the dependency graph. Bottom-up — foundations first.
  3. Slice vertically. Each task is a feature path through every layer it needs (schema + API + UI), not a horizontal layer of the system. Horizontal slicing produces half-finished branches.
  4. Write task blocks. Each task is YAML frontmatter (id, depends_on, parallel_safe, conflicts_with, files_write, files_read, branch_suffix, scope) plus prose (description, acceptance, verification). Format and field semantics: references/task-block-format.md.
  5. Order and checkpoint. Phases are presentational; the DAG is the execution order. Checkpoints are synchronization barriers — dispatch pauses until they clear.
  6. Declare the Execution DAG. Top-of-document summary of edges using → and ||. Format and dispatcher contract: references/execution-dag.md.

Universal rules

  • Stable IDs, never renumbered. Use content-based slugs (T-auth-schema). Renumbering breaks every reference. Retire dropped IDs rather than reusing them.
  • files_write is authoritative, not advisory. The dispatcher uses it for conflict detection. Under-declare → parallel collisions; over-declare → false serialization.
  • The DAG is a summary, not the source of truth. Per-task depends_on is authoritative. The verification checklist enforces that they agree.
  • Day-zero ready set must be non-empty. At least one task has depends_on: []. If none do, the plan is malformed.
  • scope: L must be split before dispatch. Agents perform best on XS / S / M.
  • Plan, do not implement. This skill never writes code. The output is a plan document; execution is a separate step.
  • Every plan carries a **Status:** line. Lifecycle proposed → in-progress → shipped | superseded. A fresh plan starts at proposed; keep it current as the work moves. It is the signal for retiring completed plans (prune shipped/superseded plans manually), so an unmarked plan never gets recognized as done. See assets/plan-document-template.md.

References

  • references/task-block-format.md — per-task YAML frontmatter and prose structure, field-by-field semantics
  • references/execution-dag.md — DAG syntax, dispatcher contract, checkpoints, worked example
  • assets/plan-document-template.md — full document template
  • references/parallelization-decisions.md — when to set each YAML field; contract-first, barrel-file, migration patterns
  • references/task-sizing-and-redflags.md — sizing table, when to split, common rationalizations, red flags

Verification

Before starting implementation, confirm:

  • The plan has a **Status:** line (a fresh plan starts at proposed)
  • Every task has a stable id (content-based slug, not a number)
  • Every task has acceptance criteria and a verification step
  • Every task declares depends_on, parallel_safe, files_write
  • Every pair of tasks whose files_write overlap is in each other's conflicts_with
  • At least one task has depends_on: [] (a non-empty day-zero ready set)
  • No task is scope: L (split it before dispatch)
  • No task touches more than ~5 files
  • The Execution DAG matches the per-task depends_on (no orphan IDs, no missing edges)
  • Checkpoints exist between major phases and are referenced in the DAG
  • The human has reviewed and approved the plan

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