Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/jpicklyk/task-orchestrator/implementnpx skills add jpicklyk/task-orchestrator --skill implementgit clone --depth 1 https://github.com/jpicklyk/task-orchestratorWhat 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 | $0.00101 | $0.11734 |
| Opus 5 | $0.00051 | $0.05867 |
| Sonnet 5 | $0.00020 | $0.02347 |
| Haiku 4.5 | $0.00010 | $0.01173 |
Grade A, and why
implement 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 2d ago.
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 — 960 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implement
End-to-end workflow for taking MCP work items from queue to PR. This skill composes the schema-driven planning (spec-quality), implementation, review (review-quality), and git/PR workflow into a single pipeline.
Usage:
/implement <item-id>— work on a specific item/implement— with context about what to work on- Can process single items or multiple items in batch
Step 1 — Assess the Work
Load the item(s) and determine the execution tier and interaction mode.
For each item, call get_context(itemId=...) to understand:
- Current role and gate status
- Schema tag (feature-implementation, bug-fix, etc.)
- Existing notes already filled
- Dependencies and blocked status
Execution tier — classify by this table (canonical source shared with the Workflow Orchestrator output style; edit the fragment, not this copy):
| Criteria | Tier | Pipeline |
|---|---|---|
| 1-2 files, known fix, no migration/new API | Direct | Orchestrator edits, tests, reviews inline |
| 3-10 files, single logical unit, clear or explorable scope | Delegated | Single subagent, separate review agent |
| 11+ files, multiple independent work streams, dependency edges | Parallel | Worktree agents, full pipeline |
Force-UP signals (bump tier regardless of file count):
- Database migration → min Delegated
- New public API surface → min Delegated
- Multiple independent work streams → Parallel
- User says "let's plan" / collaborative language → min Delegated
Force-DOWN signals:
- User says "just fix it" / "quick" → Direct (unless complexity contradicts)
- Schema tag is
defaultor absent → eligible for Direct
If the item has no schema tag, apply quick-fix for Direct tier or leave untagged for Delegated/Parallel (the default schema catches these).
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 960 lines · 101 tokens per session scan A 144e5c69e31e
implement is a skill published in the GitHub repository jpicklyk/task-orchestrator (205 stars, last pushed 28d ago), licensed MIT. It adds 101 tokens to every session and 11,734 once invoked, about $0.0005 per session on Opus 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.
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file-todos
File-based todo and task tracking in the todos/ directory. Use when creating, triaging, listing, or managing todo files, tracking work items, managing the backlog, converting PR comments to tracked tasks, or checking todo status and dependencies.
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.
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omh-feedback-triage
This is a Hermes-native feedback-triage workflow skill.
triage-sweep
Backfill labels across oh-my-hermes issues and pull requests. Run manually to sweep everything currently unlabeled, or pass a number to triage one item. Use when issues and PRs have accumulated without labels, after adding a new label to .github/labels.yml, or before a release when the backlog needs to be readable by…