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/maddhruv/absolute/absolute-worknpx skills add maddhruv/absolute --skill absolute-workgit clone --depth 1 https://github.com/maddhruv/absoluteWrote 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/maddhruv/absolute/absolute-work)<a href="https://agentmods.dev/skills/maddhruv/absolute/absolute-work"><img src="https://agentmods.dev/badge/skills/maddhruv/absolute/absolute-work.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 | $0.00104 | $0.05009 |
| Opus 5 | $0.00052 | $0.02505 |
| Sonnet 5 | $0.00021 | $0.01002 |
| Haiku 4.5 | $0.00010 | $0.00501 |
Grade A, and why
absolute-work scanned grade A with 1 finding 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 3d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
4. **How to test it** — end every session with concrete, copy-pasteable steps the user can run to exercise the added functionality themselves: the exact commands to start the app/script, the inputs or routes to hit (`cur How it starts
The opening of the file, as written. The whole thing — 409 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Start your first response with the 🛠️ emoji.
Absolute Work: End-to-End AI Development Lifecycle
Absolute Work takes any unit of work — a ticket, a task, a plan, a migration — from fuzzy intent to verified code. It is one continuous skill with hard gates between phases: brainstorm a shared design, write and review a spec, decompose into a dependency-graphed task board, then peel tasks off one safe wave at a time with test-first verification. Nothing is assumed, nothing is silently expanded, and no code is written until the design is approved.
The lifecycle has 6 phases: INTAKE & BRAINSTORM → SPEC → DECOMPOSE & PLAN → EXECUTE → VERIFY → CONVERGE
The Phase Gate Rule
Absolute Work STOPS at the end of every phase and waits for the user's explicit "go" before advancing. This is non-negotiable. The phases are:
INTAKE & BRAINSTORM ─┃ gate ┃─ SPEC ─┃ gate ┃─ DECOMPOSE & PLAN ─┃ gate ┃─ EXECUTE ─┃ gate per wave ┃─ VERIFY ─┃ gate ┃─ CONVERGE
At each gate, present what was produced, summarize what comes next, and ask the user
to confirm before proceeding. Never chain two phases without an approval in between.
Use AskUserQuestion (where available) for every gate and every interview question.
Activation Protocol
Immediately after the banner, enter plan mode before doing anything else:
- On platforms with native plan mode (e.g. Claude Code's
EnterPlanMode): invoke it immediately. - On platforms without it: simulate plan mode — complete INTAKE & BRAINSTORM and SPEC fully, write no code, and get explicit approval before EXECUTE.
The first three phases are planning work. No files are created or modified (other than the spec and the board) until the user approves the task graph and execution begins.
Session Resume Protocol
When Absolute Work is invoked and a .absolute-work/board.md already exists in the project root:
- Detect: Read the board and determine its status.
- Display: Print a compact summary of completed / in-progress / blocked / remaining tasks.
- Resume: Pick up from the last incomplete wave — do NOT restart from INTAKE.
- Reconcile: If the codebase changed since the last session, diff against the board's expected state and flag conflicts before resuming.
What ships with it
7 files 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.
- 3d ago First seen · 409 lines · 104 tokens per session scan A 6e0bdca0ebef
absolute-work is a skill published in the GitHub repository maddhruv/absolute (209 stars, last pushed 1mo ago), licensed MIT. It adds 104 tokens to every session and 5,009 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
test-driven-development
Use when implementing any feature or bugfix, before writing implementation code.
data-engineering
Skill "data-engineering" from fengshao1227/ccg-workflow, covering 数据工程域 · data engineering, 域概览, 数据管道编排, 框架对比 and airflow 核心模式.
mobile
移动开发。iOS、Android、SwiftUI、Jetpack Compose、React Native、Flutter、跨平台。当用户提到移动开发、iOS、Android、跨平台时路由到此。.
infrastructure
云原生基础设施。Kubernetes、Helm、Kustomize、Operator、CRD、GitOps、ArgoCD、Flux、IaC、Terraform、Pulumi、CDK。当用户提到 K8s、Helm、GitOps、IaC 时路由到此。.
animate
Review a feature and enhance it with purposeful animations, micro-interactions, and motion effects that improve usability and delight. Use when the user mentions adding animation, transitions, micro-interactions, motion design, hover effects, or making the UI feel more alive.
agent-integration
Run all three agent integration phases sequentially: research, write-tests, and implement using E2E-first TDD (unit tests written last). For individual phases, use /agent-integration:research, /agent-integration:write-tests, or /agent-integration:implement. Use when the user says "integrate agent", "add agent…