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/dremonkey/agents-and-skills/exec-eng-tasksnpx skills add dremonkey/agents-and-skills --skill exec-eng-tasksgit clone --depth 1 https://github.com/dremonkey/agents-and-skillsWrote 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/dremonkey/agents-and-skills/exec-eng-tasks)<a href="https://agentmods.dev/skills/dremonkey/agents-and-skills/exec-eng-tasks"><img src="https://agentmods.dev/badge/skills/dremonkey/agents-and-skills/exec-eng-tasks.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00071 | $0.03749 |
| Opus 5 | $0.00036 | $0.01875 |
| Sonnet 5 | $0.00014 | $0.00750 |
| Haiku 4.5 | $0.00007 | $0.00375 |
Grade A, and why
exec-eng-tasks 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 5d 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 — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Execute Engineering Tasks
This skill implements an approved engineering plan by dispatching sub-agents to carry out task files. It is the execution counterpart to plan-eng-tasks, which handles planning.
Input contract
This skill expects artifacts already produced by plan-eng-tasks:
- Epic file:
tasks/<EPIC_NAME>/EPIC.md— source of truth for goal, architecture overview, task list, key decisions, and anti-goals. - Task files:
tasks/<EPIC_NAME>/<task>.md— one per implementable unit, following the task template (title, status, dependencies, goal, context, implementation steps, acceptance criteria). - Architecture docs (optional): relevant docs in
docs/architecture/— organized by system or topic, referenced by tasks when relevant.
If these artifacts do not exist, stop and tell the user to run plan-eng-tasks first.
Engineering preferences (included in sub-agent prompts)
Read skills/shared/engineering-preferences.md and include its contents in every sub-agent prompt.
Status markers
Task and epic files use these status markers:
[ ]— pending[~]— in progress[x]— done[!]— failed / blocked
Closed tasks directory
Tasks that are completely done ([x]) or cancelled should be moved into a _closed/ subdirectory within the epic (e.g., tasks/<EPIC_NAME>/_closed/<task>.md). This keeps the epic directory clean — only active/pending work is visible at a glance. When reviewing or listing tasks, ignore everything in _closed/ unless the user explicitly asks to check closed tasks.
Step 1: Present the implementation plan
Display a clear execution plan showing:
IMPLEMENTATION PLAN
===================
Execution order (respecting dependencies):
[1] tasks/<EPIC_NAME>/<task-1>.md — <title> (small)
[2] tasks/<EPIC_NAME>/<task-2>.md — <title> (medium)
└── blocked by: [1]
[3] tasks/<EPIC_NAME>/<task-3>.md — <title> (small)
└── blocked by: [1]
[4] tasks/<EPIC_NAME>/<task-4>.md — <title> (large)
└── blocked by: [2], [3]
Parallel execution groups:
Group A (no dependencies): [1]
Group B (after [1]): [2], [3] ← will run in parallel
Group C (after [2],[3]): [4]
Estimated sub-agents: ___
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.
- 5d ago First seen · 270 lines · 71 tokens per session scan A 41a548811566
exec-eng-tasks is a skill published in the GitHub repository dremonkey/agents-and-skills (2 stars, last pushed 22d ago), licensed MIT. It adds 71 tokens to every session and 3,749 once invoked, about $0.0004 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…