Borrowing it
Nothing to install: this file belongs to jpicklyk/task-orchestrator. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/jpicklyk/task-orchestrator/main/.claude/skills/feature-implementation/SKILL.mdgit clone --depth 1 https://github.com/jpicklyk/task-orchestratorWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jpicklyk/task-orchestrator/feature-implementation)<a href="https://agentmods.dev/skills/jpicklyk/task-orchestrator/feature-implementation"><img src="https://agentmods.dev/badge/skills/jpicklyk/task-orchestrator/feature-implementation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jpicklyk/task-orchestrator/feature-implementation"><img src="https://agentmods.dev/badge/skills/jpicklyk/task-orchestrator/feature-implementation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00112 | $0.02172 |
| Opus 5.5 | $0.00045 | $0.00869 |
| Sonnet 5.5 | $0.00022 | $0.00434 |
| Haiku 4.5 | $0.00011 | $0.00217 |
Grade A, and why
feature-implementation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 251 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Implementation Workflow
End-to-end workflow for a feature-implementation tagged item — the feature container
that holds the plan and holistic review. Child work items under this container use the
feature-task tag with lighter gates (task-scope instead of the feature-level
feature-summary, and no review phase by default — task-level review is opt-in via the
needs-task-review trait, which adds a review-checklist note to that child). A second
child-level trait, needs-test-author, is opt-in the same way (applied per the
/implement Step 1 trigger rule) and adds its own gate-enforced notes.
Covers all three phases (queue → work → review) with gate-enforced notes at each transition.
Usage: /feature-implementation [item-uuid]
- If
item-uuidis provided: load the existing item and resume from its current phase - If omitted: create a new item and start from the beginning
Phase 0 — Setup
If an item UUID was provided, call:
get_context(itemId="<uuid>")
Check canAdvance and missingRequiredNotes to determine which phase the item is in,
then jump to the appropriate phase below.
If no UUID was provided, create the item:
manage_items(
operation="create",
items=[{ title: "<feature title>", tags: "feature-implementation", priority: "medium" }]
)
Note the returned UUID and expectedNotes list. Confirm the item is in queue role,
then continue to Phase 1.
Phase 1 — Queue: Define the Feature Summary
Goal: Fill the single required queue-phase note before advancing to work.
1a. Fill feature-summary
Use manage_notes to upsert the feature-summary note:
manage_notes(
operation="upsert",
notes=[{
itemId: "<uuid>",
key: "feature-summary",
role: "queue",
body: "<content>"
}]
)
What to write: Keep this note lean (target under 2k chars) — it stays at the feature level, not the child-task level where the full spec-quality disciplines apply. Cover:
- Goal — the problem this solves and who benefits.
- Findings → tasks table — a table mapping each finding or requirement to the child task that will address it.
- Dependency edges — ordering constraints between child tasks, if any.
- Non-goals pointer — a reference to where non-goals are documented per child (each
child's
task-scopenote carries its own alternatives/non-goals/blast-radius/risk/test strategy per the spec-quality framework); this note does not repeat that analysis.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today Changed · +2 lines 2d3ae7524c77
- 1mo ago First seen · 249 lines · 112 tokens per session scan A 89110352666c
feature-implementation is a skill published in the GitHub repository jpicklyk/task-orchestrator (208 stars, last pushed today), licensed MIT. It adds 112 tokens to every session and 2,172 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
branch-surgery-pr-split
Split oversized or mixed-concern branches into smaller, reviewable PR stacks with safety refs, topology selection, parity audits, and merge sequencing. Use when a PR or branch is too large, difficult to review, mixed across concerns, conflict-prone, or needs to be decomposed without losing net changes.
do-it
Turn the current discussion into a task step and implement it — adds step to task file, updates spec if needed, then implements with review-fix loop.
plan-tasks
Read an existing spec and propose a task breakdown — assesses separable work streams, proposes split, creates task files linked to the spec.
draft-issue
Draft a GitHub issue based on a discussion or requirements in the current conversation.
finish-task
Deprecated alias for close-task.
run-task
Run pending steps, then aftertask finalization; does not close the task.