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End-to-end, phase-gated SDLC for AI coding agents: relentless design interview → reviewed spec → dependency-graphed task board → safe-wave TDD execution → verification → converge. Handles features, bugs, refactors, greenfield projects, planning breakdowns, and migrations. Trigger
End-to-end, phase-gated SDLC for AI coding agents: relentless design interview → reviewed spec → dependency-graphed task board → safe-wave TDD execution → verification → converge. Handles features, bugs, refactors, greenfield projects, planning breakdowns, and migrations. Triggers on "absolute work", "build this end-to-end", "plan and build", "break this into tasks", "grill me on this plan", "pick up this ticket", "run this migration".
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Start your first response with the 🛠️ emoji.
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
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.
Immediately after the banner, enter plan mode before doing anything else:
EnterPlanMode): invoke it immediately.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.
When Absolute Work is invoked and a .absolute-work/board.md already exists in the project root:
If the board is completed, ask whether to start a new session (archive the old board to
.absolute-work/archive/) or review the finished work. Never blow away an existing board
without explicit user confirmation.
Before INTAKE begins, auto-detect the project's conventions so every phase is grounded
in reality, not assumptions. If .absolute.config.json or ~/.absolute/config.json exists
(from /absolute init), resolve the effective config (project file → global projects["<cwd>"]
→ global defaults), read its cached conventions first, and detect only what's missing. The
preferences (tdd, autonomy, specDir, boardTracking) likewise drive later phases.
| Signal | Files to Check |
|---|---|
| Package manager | package-lock.json (npm), yarn.lock, pnpm-lock.yaml, bun.lockb, Cargo.lock, go.sum |
| Language/Runtime | tsconfig.json, pyproject.toml / setup.py, go.mod, Cargo.toml |
| Test runner | jest.config.*, vitest.config.*, pytest.ini, .mocharc.*, test directory patterns |
| Linter/Formatter | .eslintrc.*, eslint.config.*, .prettierrc.*, ruff.toml, .golangci.yml |
| Build system | Makefile, vite.config.*, next.config.*, turbo.json |
| CI/CD | .github/workflows/, .gitlab-ci.yml, Jenkinsfile |
| Available scripts | scripts in package.json, Makefile targets |
| Directory conventions | src/, lib/, app/, tests/, __tests__/, spec/ |
Write detected conventions to the board under ## Project Conventions. Reference them in
every later phase — especially PLAN and the mandatory verification tail tasks. Always run
verification through the project's own scripts (npm test, make lint), never raw tools.
Use Absolute Work when:
Do NOT use Absolute Work when:
references/execution-model.md.).absolute-work/board.md, surviving across sessions.Turn fuzzy intent into a shared, bulletproof design. This is a structured interrogation of every assumption, dependency, and design branch — not a casual chat.
The interview directive — operate by this verbatim:
Interview me relentlessly about every aspect of this plan until we reach a shared understanding. Walk down each branch of the design tree, resolving dependencies between decisions one-by-one. For each question, provide your recommended answer.
Ask the questions one at a time.
If a question can be answered by exploring the codebase, explore the codebase instead.
Read what exists before asking anything: docs/ (README first), root README.md, CLAUDE.md,
CONTRIBUTING.md, docs/plans/ (overlapping designs), recent commits (last 10-20), package
manifests, top-level structure. Synthesize what matters — do not dump a file listing.
Before asking ANY question, check if the codebase answers it. Facts live in code
(database, test framework, auth); preferences require asking (visual style, real-time vs batch).
When code answers it, state what you found: "I see you're using Prisma with PostgreSQL — I'll
design around that." See references/intake-playbook.md.
Identify the type and swap in its tailored question bank (full banks in references/intake-playbook.md):
| Type | Focus |
|---|---|
| Feature | user problem, flow, happy/error paths, scope boundary |
| Bug | repro steps, expected vs actual, blast radius, fix criteria |
| Refactor | pain point, target state, blast radius, test safety net, incremental vs all-at-once |
| Greenfield | problem/user fit, v1 scope, stack, data model, deploy target |
| Planning / breakdown | goal, milestones, sequencing, what ships first |
| Migration | what→what, coexistence, rollback, breaking changes, call-site inventory — load references/migration-playbook.md |
If the request spans multiple independent subsystems, flag it and decompose into sub-projects first; brainstorm the first sub-project through the normal flow.
AskUserQuestion. Never batch.Before presenting the design, review every decision: am I 100% sure, or filling gaps with assumptions? Any sub-100% decision → return to the interview. State your confidence to the user.
Present section by section (architecture, components, data flow, error handling, testing), scaled to complexity. Get approval per section. Design for isolation: small units, one clear purpose each, well-defined interfaces. Follow existing patterns; don't fight the codebase.
━━ GATE: user approves the full design before Phase 2. ━━
Write the approved design to docs/plans/YYYY-MM-DD-<topic>-design.md (clear prose, file
paths, code blocks for schemas/interfaces, a Decision Log). Scale sections to complexity.
Then run a scored spec review with a separate reviewer subagent (generator-evaluator separation): graded on Completeness, Consistency, Clarity, Scope, Testability (1-5 each).
See references/spec-writing.md for the template, scaling rules, and review rubric.
━━ GATE: user reviews and approves the spec before Phase 3. ━━
Break the spec into atomic sub-tasks, build the dependency graph, and write the board.
Each sub-task has: ID (AW-001), Title (action-oriented), Description (2-3 sentences),
Type (code | test | docs | infra | config), Size (S < 50 lines | M 50-200;
no L — decompose further), Dependencies (task IDs).
Rules: test tasks separate from code; infra/config before dependents; aim for 5-15 tasks; every
graph ends with the three mandatory tail tasks (Self Code Review → Requirements Validation →
Full Project Verification — see references/verification-framework.md). Apply the complexity budget:
if scope exceeds ~15 M-equivalent tasks, suggest splitting into multiple sessions.
Compute each task's depth (max(dependency depth) + 1) and group by depth into waves. Then apply
the safety pass: with
name: absolute-work version: 0.5.0 description: > End-to-end, phase-gated SDLC for AI coding agents: relentless design interview → reviewed spec → dependency-graphed task board → safe-wave TDD execution → verification → converge. Handles features, bugs, refactors, greenfield projects, planning breakdowns, and migrations. Triggers on "absolute work", "build this end-to-end", "plan and build", "break this into tasks", "grill me on this plan", "pick up this ticket", "run this migration". category: workflow tags: - workflow - sdlc - planning - tdd - spec - specification platforms: - claude-code - gemini-cli - openai-codex - mcp user-invocable: true argument-hint: "[target]" license: MIT maintainers: - github: maddhruv
--- name: absolute-work version: 0.5.0 description: > End-to-end, phase-gated SDLC for AI coding agents: relentless design interview → reviewed spec → dependency-graphed task board → safe-wave TDD execution → verification → converge. Handles features, bugs, refactors, greenfield projects, planning breakdowns, and migrations. Triggers on "absolute work", "build this end-to-end", "plan and build", "break this into tasks", "grill me on this plan", "pick up this ticket", "run this migration". category: workflow tags: - workflow - sdlc - planning - tdd - spec - specification platforms: - claude-code - gemini-cli - openai-codex - mcp user-invocable: true argument-hint: "[target]" license: MIT maintainers: - github: maddhruv --- > 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: 1. **On platforms with native plan mode** (e.g. Claude Code's `EnterPlanMode`): invoke it immediately. 2. **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: 1. **Detect**: Read the board and determine its status. 2. **Display**: Print a compact summary of completed / in-progress / blocked / remaining tasks. 3. **Resume**: Pick up from the last incomplete wave — do NOT restart from INTAKE. 4. **Reconcile**: If the codebase changed since the last session, diff against the board's expected state and flag conflicts before resuming. If the board is `completed`, ask whether to start a new session (archive the old board to `.absolute-work/archive/`) or review the finished work. **Never blow away an existing board without explicit user confirmation.** --- ## Codebase Convention Detection **Before INTAKE begins**, auto-detect the project's conventions so every phase is grounded in reality, not assumptions. If `.absolute.config.json` or `~/.absolute/config.json` exists (from `/absolute init`), resolve the effective config (project file → global `projects["<cwd>"]` → global `defaults`), read its cached `conventions` first, and detect only what's missing. The `preferences` (`tdd`, `autonomy`, `specDir`, `boardTracking`) likewise drive later phases. | Signal | Files to Check | |---|---| | **Package manager** | `package-lock.json` (npm), `yarn.lock`, `pnpm-lock.yaml`, `bun.lockb`, `Cargo.lock`, `go.sum` | | **Language/Runtime** | `tsconfig.json`, `pyproject.toml` / `setup.py`, `go.mod`, `Cargo.toml` | | **Test runner** | `jest.config.*`, `vitest.config.*`, `pytest.ini`, `.mocharc.*`, test directory patterns | | **Linter/Formatter** | `.eslintrc.*`, `eslint.config.*`, `.prettierrc.*`, `ruff.toml`, `.golangci.yml` | | **Build system** | `Makefile`, `vite.config.*`, `next.config.*`, `turbo.json` | | **CI/CD** | `.github/workflows/`, `.gitlab-ci.yml`, `Jenkinsfile` | | **Available scripts** | `scripts` in `package.json`, `Makefile` targets | | **Directory conventions** | `src/`, `lib/`, `app/`, `tests/`, `__tests__/`, `spec/` | Write detected conventions to the board under `## Project Conventions`. Reference them in every later phase — especially PLAN and the mandatory verification tail tasks. Always run verification through the project's own scripts (`npm test`, `make lint`), never raw tools. --- ## When to Use This Skill **Use Absolute Work when:** - Picking up a ticket or task that needs design before implementation - Multi-step feature development touching 3+ files or components - "Build this end-to-end", "plan and execute this", "break this into tasks" - Greenfield projects, major refactors, or **migrations** - Planning/breakdown work — turning a vague goal into a sequenced task list - Complex bug fixes spanning multiple systems - The user wants to be grilled on a design before building **Do NOT use Absolute Work when:** - Single-file bug fixes or typo corrections where the answer is obvious - Quick questions, code explanations, or pure research - Tasks the user explicitly wants to drive manually --- ## Key Principles 1. **Phase gates always.** Stop and get explicit approval between every phase. Control over speed. 2. **Codebase before questions.** Search the code first; only ask what code genuinely cannot answer. 3. **Relentless until aligned.** Interview one question at a time until BOTH you and the user are 100% confident. Doubt on either side means keep going. 4. **Spec before code.** No implementation until a written spec is reviewed and approved. 5. **Dependency-first decomposition.** Every task is a node in a DAG, not a flat list. 6. **Safety-first execution.** Blockers and dependents run **sequentially**; only **provably-independent** tasks parallelize. When in doubt, serialize. (See `references/execution-model.md`.) 7. **Test-first verification.** Every task writes tests before implementation. "Done" means tests pass. 8. **Generator ≠ evaluator.** The agent that builds a task does not grade it. 9. **Persistent state.** All progress lives in `.absolute-work/board.md`, surviving across sessions. 10. **No silent scope creep.** Everything outside the agreed scope goes to Deferred Work, visible on the board. 11. **Never auto-commit.** Suggest a commit; the user commits. --- ## Phase 1: INTAKE & BRAINSTORM (Relentless Design Interview) Turn fuzzy intent into a shared, bulletproof design. This is a structured interrogation of every assumption, dependency, and design branch — not a casual chat. **The interview directive — operate by this verbatim:** > Interview me relentlessly about every aspect of this plan until we reach a shared understanding. Walk down each branch of the design tree, resolving dependencies between decisions one-by-one. For each question, provide your recommended answer. > > Ask the questions one at a time. > > If a question can be answered by exploring the codebase, explore the codebase instead. ### Step 1 — Deep context scan Read what exists before asking anything: `docs/` (README first), root `README.md`, `CLAUDE.md`, `CONTRIBUTING.md`, `docs/plans/` (overlapping designs), recent commits (last 10-20), package manifests, top-level structure. Synthesize what matters — do not dump a file listing. ### Step 2 — Codebase-first intelligence **Before asking ANY question, check if the codebase answers it.** Facts live in code (database, test framework, auth); preferences require asking (visual style, real-time vs batch). When code answers it, state what you found: "I see you're using Prisma with PostgreSQL — I'll design around that." See `references/intake-playbook.md`. ### Step 3 — Detect the work TYPE and adapt Identify the type and swap in its tailored question bank (full banks in `references/intake-playbook.md`): | Type | Focus | |---|---| | **Feature** | user problem, flow, happy/error paths, scope boundary | | **Bug** | repro steps, expected vs actual, blast radius, fix criteria | | **Refactor** | pain point, target state, blast radius, test safety net, incremental vs all-at-once | | **Greenfield** | problem/user fit, v1 scope, stack, data model, deploy target | | **Planning / breakdown** | goal, milestones, sequencing, what ships first | | **Migration** | what→what, coexistence, rollback, breaking changes, call-site inventory — **load `references/migration-playbook.md`** | ### Step 4 — Scope assessment If the request spans multiple independent subsystems, flag it and decompose into sub-projects first; brainstorm the first sub-project through the normal flow. ### Step 5 — Relentless interview - **One question at a time** via `AskUserQuestion`. Never batch. - **Strictly linear** — resolve decision A before asking about dependent decision B. - **Walk the design tree depth-first** — purpose → data model → behavior → UI → edge cases. Every branch has an error/edge-case child; walk it. - **Honest options** — only propose multiple approaches at a genuine fork; always mark one **(Recommended)** with rationale tied to project context. When the answer is obvious, present it and briefly say why alternatives were dismissed. - **Mutual 100% confidence** — after each decision, confirm both sides are sure. Hesitation means probe deeper. ### Step 6 — Confidence self-check Before presenting the design, review every decision: am I 100% sure, or filling gaps with assumptions? Any sub-100% decision → return to the interview. State your confidence to the user. ### Step 7 — Design presentation Present section by section (architecture, components, data flow, error handling, testing), scaled to complexity. Get approval per section. Design for isolation: small units, one clear purpose each, well-defined interfaces. Follow existing patterns; don't fight the codebase. **━━ GATE: user approves the full design before Phase 2. ━━** --- ## Phase 2: SPEC (Spec-Driven Development) Write the approved design to `docs/plans/YYYY-MM-DD-<topic>-design.md` (clear prose, file paths, code blocks for schemas/interfaces, a Decision Log). Scale sections to complexity. Then run a **scored spec review** with a *separate* reviewer subagent (generator-evaluator separation): graded on Completeness, Consistency, Clarity, Scope, Testability (1-5 each). - **4.0+** → approved, proceed to user review - **3.0-3.9** → fix flagged issues, re-dispatch (max 3 iterations) - **< 3.0** → surface to the user immediately See `references/spec-writing.md` for the template, scaling rules, and review rubric. **━━ GATE: user reviews and approves the spec before Phase 3. ━━** --- ## Phase 3: DECOMPOSE & PLAN (Build the Task Board) Break the spec into atomic sub-tasks, build the dependency graph, and write the board. ### Decompose Each sub-task has: **ID** (`AW-001`), **Title** (action-oriented), **Description** (2-3 sentences), **Type** (`code` | `test` | `docs` | `infra` | `config`), **Size** (`S` < 50 lines | `M` 50-200; no `L` — decompose further), **Dependencies** (task IDs). Rules: test tasks separate from code; infra/config before dependents; aim for 5-15 tasks; every graph ends with the three **mandatory tail tasks** (Self Code Review → Requirements Validation → Full Project Verification — see `references/verification-framework.md`). Apply the complexity budget: if scope exceeds ~15 M-equivalent tasks, suggest splitting into multiple sessions. ### Build the DAG and assign safe waves Compute each task's depth (`max(dependency depth) + 1`) and group by depth into waves. Then apply the **safety pass**: with
Skill source recorded
Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.
Review before install: Avoid automatic install
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Quality
64/100
Promising
Trust
60/100
Sandbox only
Audit
73/100
Risky
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
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"Permission surface needs review: shell or command execution, filesystem or document access",
"Stars/forks activity: 211 stars, 30 forks; issue activity unavailable in current metadata",
"Permission surface: shell or command execution, filesystem or document access"
]
},
"agent_proven": {
"version": "agent-proven-v1",
"score": 0,
"tier": "unproven",
"label": "Needs first agent run",
"summary": "No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.",
"metrics": {
"totalOutcomes": 0,
"successfulOutcomes": 0,
"failedOutcomes": 0,
"installAttempts": 0,
"installSuccessRate": null,
"successRate": null,
"recentSuccessRate": null,
"recentFailureRate": null,
"riskBlocked": 0,
"setupRequired": 0,
"notRelevant": 0,
"avgOutputQuality": null,
"avgTimeToUsefulMs": null,
"productionOutcomes": 0,
"humanReviewRequired": 0,
"uniqueAgents": 0,
"lastOutcomeAt": null
},
"signals": [],
"penalties": [
"No real agent outcome evidence yet"
]
},
"audit": {
"score": 73,
"risk_level": "risky",
"risk_label": "Risky",
"warnings": [
"Permission surface may require sandboxing",
"Financial research output is not financial advice; require human review before any live investment decision",
"Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required",
"The SKILL.md is very long and dense; some users may find it overwhelming, but the structure is clear.",
"The skill relies on user approval at each gate, which is safe but may slow down autonomous workflows.",
"Financial research output is not financial advice; require human review before any live investment decision.",
"This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.",
"Quality score needs review"
]
},
"safety_gate": {
"tier": "blocked",
"label": "Blocked for auto-install",
"auto_install_policy": "block",
"auto_install_allowed": false,
"human_review_required": true,
"blocked": true,
"recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
},
"quality": {
"score": 64,
"label": "Promising"
},
"supply": {
"track": "Coding and developer agents",
"scenario": "Coding agents",
"maintenance": "2mo since push",
"risk": "Risky"
},
"alternative_skills": [
{
"slug": "maddhruv-absolute-ui",
"name": "absolute-ui",
"url": "https://www.openagentskill.com/skills/maddhruv-absolute-ui",
"stars": 211,
"install_command": "npx skills add maddhruv/absolute --skill absolute-ui",
"trust_score": 72,
"audit_score": 75
},
{
"slug": "maddhruv-absolute-docs",
"name": "absolute-docs",
"url": "https://www.openagentskill.com/skills/maddhruv-absolute-docs",
"stars": 211,
"install_command": "npx skills add maddhruv/absolute --skill absolute-docs",
"trust_score": 71,
"audit_score": 74
}
],
"do_not_use_when": [
"teams that need a vendor-supported SLA",
"production agents without a repository review",
"The SKILL.md is very long and dense; some users may find it overwhelming, but the structure is clear.",
"No OpenAgentSkill engagement data yet",
"Audit risk risky exceeds max_risk=medium",
"High-risk permission hints: Shell or command execution, Secrets or environment access",
"Permission surface may require sandboxing",
"Financial research output is not financial advice; require human review before any live investment decision"
],
"agent_contract": {
"task_input": "Use absolute-work in an agent workflow",
"recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
"install_policy": "block",
"minimum_review_before_use": [
"Trust: 68/100 Manual review",
"Audit: 73/100 Risky",
"Safety: 29/100 Avoid automatic install",
"Review repository, license, install command, and permission surface before production use."
],
"expected_agent_output": {
"selected_skill": "maddhruv-absolute-work (absolute-work)",
"install_command": "npx skills add maddhruv/absolute --skill absolute-work",
"risk_summary": "Risky; Blocked for auto-install; Review before production",
"verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
}
},
"outcome_feedback": {
"endpoint": "https://www.openagentskill.com/api/agent/outcome",
"method": "POST",
"requires_resolve_event_id": true,
"event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
"expected_outcomes": [
"success",
"failed",
"not_relevant",
"blocked_by_risk",
"setup_required"
],
"payload_template": {
"event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
"skill_slug": "maddhruv-absolute-work",
"task": "Use absolute-work in an agent workflow",
"agent": "codex",
"outcome": "success",
"install_used": true,
"risk_blocked": false,
"setup_required": false,
"task_success": true,
"output_quality": 4,
"error_type": null,
"human_review_required": false,
"workspace": "sandbox",
"time_to_useful_ms": 120000,
"notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
}
},
"endpoints": {
"web": "https://www.openagentskill.com/skills/maddhruv-absolute-work",
"api": "https://www.openagentskill.com/api/agent/skills/maddhruv-absolute-work",
"audit": "https://www.openagentskill.com/skills/maddhruv-absolute-work/audit",
"eval": "https://www.openagentskill.com/api/agent/evals?slug=maddhruv-absolute-work&task=Use%20absolute-work%20in%20an%20agent%20workflow&max_risk=medium",
"resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20absolute-work%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
"receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20absolute-work%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
"install": "https://www.openagentskill.com/api/skills/maddhruv-absolute-work/install",
"manifest": "https://www.openagentskill.com/api/registry/manifest/maddhruv-absolute-work"
}
}Listing source
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