Task Create

task_create

taskcreate is the focused on-ramp for adding a single item to the project's tasks/ backlog. Its one job is to turn a single request into one conformant, lint-clean task file with no surrounding workflow. It is a thin, trigger-precise front end over the task skill: the task skill stays the authority for the file format and the create mechanics, and taskcreate lets a one-shot "make a task for X" load a narrow surface instead of the whole backlog-management skill.

Activate when the user wants exactly one task file written:

• "Make / create / add / file / write a task (or todo) for X."
• "Capture this as a task" about a single piece of upcoming work.
• A single follow-up item that surfaced mid-conversation and should persist as one task file.

Route to the task skill instead when the user wants to list, query, update, refine, finish, implement, defer, archive, or lint tasks, or to derive several tasks from a larger document in one pass — those are the broader backlog workflows. Route to task_auto_check when the user wants an existing task repaired until task_check reports ready. Route to task_select when the user wants a recommendation about what backlog item to work on next.

The task skill's SKILL.md is the single source of truth; keep every shared rule there and follow it rather than copying it. Read that skill and apply:

• ` — , (including the date-stamped created / updated), , and the ` sections.
• ` — locate or scaffold tasks/ through the bundled discovertasks.sh / inittasks.sh`.
• `'s ` — the two-tier duplicate / already-done gate run before writing.
• `'s ` — the source-fidelity contract that fires whenever a task is derived from source material. This single-task on-ramp is the single-task-from-a-source path that contract names, so apply it verbatim from the base skill rather than restating it here, keeping the two in step.
• `` — the lens the drafted body is self-checked against before the file is written.
• ` — the bundled lint.py` and what each finding means.

These assets ship in the same plugin as taskcreate, so they are present wherever taskcreate is.

The bundled scripts (discover_tasks.sh, init_tasks.sh, lint.py) ship in scripts/ next to the base task skill's SKILL.md, not next to this one. After reading that base SKILL.md (per `), resolve each script's absolute path by combining the directory you loaded it from with scripts/ and invoke that absolute path — never a bare scripts/..., which resolves against the current working directory (the target project) rather than the skill, and so finds the project's own scripts/` or nothing. If the first invocation reports a missing file, re-resolve the absolute path once before treating the script as failed.

Create one file, in order:

1. Discover. Run the task skill's ` step to resolve tasks/`, scaffolding it when it is missing.
2. Gather. Confirm the single item to capture and collect enough context to fill the `` sections to the base skill's self-sufficiency bar: the file on its own is enough to implement, with everything actually available at implementation time — the codebase, the project's standing instructions, the user — staying in play. When the context is too thin for that, ask one sharp clarifying question, then proceed.
3. Prior-art gate. Run the task skill's ` step: a fast rg scan of tasks/ + tasks/archive/` that escalates to an in-depth project analysis only when the scan hits. When a match shows the work is already an open task, partially covered, already implemented, or already deferred, surface it with evidence and let the user decide how to proceed before writing — never auto-resolve.
4. Scope and name. Pick a ` from the groupings already present in tasks/, and a compact that is unique across both tasks/ and tasks/archive/`. List both directories once to keep the name collision-free.
5. Timestamp. Run date +%Y-%m-%dT%H:%M:%S once and use its output verbatim for both created and updated.
6. Self-check the draft. Judge the drafted body against the task skill's ` and resolve every finding before writing, so the file written already passes the lens task_check` will apply.
7. Write. Create /_.md with status: open and reported-by resolved via the base skill's `, then write a body that opens with a single # Title and fills Goal / Context / Approach / Acceptance per the task skill's . When filling ## Context and any cross-references, apply the cross-link discipline and the soft-pointer rule from the task skill's `, so each link to another task earns its place and each pointer to file content survives edits to its target.
8. Lint. Run the linter per the task skill's ` step (lint.py --quiet`) and resolve every blocking finding before reporting the file as created.

When this one task is derived from source material — a pasted note, a chat turn, a todo.md, a PDF, any pre-existing body of meaning — apply the task skill's `` contract on your own before reporting done: confirm the single task carries every relevant unit of meaning from that source, propagate source-wide content into it, and leave the source's keep/drop disposition to the user. A single task does not exempt the check — one source can hold more meaning than it captures.

Keep this to one atomic task file. When the request actually carries several independent items, or a single item would run past 300 lines, hand the multi-task split to the task skill rather than expanding the work here. A request that fits the base skill's Scope sizing rule stays eligible for this single-file path even when it touches multiple related parts.

Report the relative path of the one task file created and confirm the linter came back clean. Surface any assumption you made about scope, name, or body so the user can correct it. When the prior-art gate found a match, report the classification and evidence and reflect the user's decision instead of silently creating a duplicate.

The task_* family — each sibling does one job, then points to the next; the base task skill is the hub that can do all of it:

• task_create — write one task file (this skill)
• task_check — readiness gate before building (read-only)
• task_auto_check — autonomously repair one task until task_check reports ready
• task_explain — explain one task at a high level (read-only)
• task_select — choose and rank the next eligible task/action (read-only)
• task_implement — do the work
• task_audit — verify a believed-done task against the codebase (read-only)
• task_finish — close out: set status, bump updated, archive
• task_fix — audit and repair the whole tasks tree

These ship together as a family; any sibling may be absent if a deployment excluded it. The default manual chain is create → check → select → implement → audit → finish, with task_auto_check as an opt-in readiness repair loop and fix maintaining the tree.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: theafh
• Source: theafh/ai-modules
• License: MIT

Install and usage instructions live in the source repository linked above.