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/matrixfounder/agentic-development/planning-decision-treenpx skills add MatrixFounder/Agentic-development --skill planning-decision-treegit clone --depth 1 https://github.com/MatrixFounder/Agentic-developmentWrote 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/matrixfounder/agentic-development/planning-decision-tree)<a href="https://agentmods.dev/skills/matrixfounder/agentic-development/planning-decision-tree"><img src="https://agentmods.dev/badge/skills/matrixfounder/agentic-development/planning-decision-tree.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 | $0.00016 | $0.00426 |
| Opus 5 | $0.00008 | $0.00213 |
| Sonnet 5 | $0.00003 | $0.00085 |
| Haiku 4.5 | $0.00002 | $0.00043 |
Grade A, and why
planning-decision-tree 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 4d 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.
What it actually says
Planning Decision Tree
1. Task Breakdown Strategy
Core Logic: Stub-First & E2E
CRITICALLY IMPORTANT: You must split every functional requirement into two distinct task types:
-
Phase 1: Structure & Stubs
- Goal: Create file structure, class definitions, method signatures, and STUBS.
- Action:
return Noneor hardcoded values. - Verification: Write E2E test that passes on these stubs (asserting hardcoded values).
- Task Tag:
[STUB CREATION]
-
Phase 2: Logic Implementation
- Goal: Replace stubs with real logic.
- Action: Implement algorithms, DB queries, API calls.
- Verification: Update E2E test to assert real values. Add Unit Tests.
- Task Tag:
[LOGIC IMPLEMENTATION]
Decision Rule:
- IF task involves writing code -> Split into Stub + Impl.
- IF task is configuration/setup -> Single task.
2. Decomposition Levels
- Too Complex? (e.g., "Implement Auth") -> Break into "User Model", "Registration Service", "Login Service".
- Too Simple? (e.g., "Add one field") -> Combine with related tasks if safe.
- Dependency? -> Plan dependencies (Models, DB) BEFORE dependent services.
3. Concreteness Rules
- For New Projects: Define directory structure, class names, method signatures.
- For Modifications: Specify exact file paths and methods to change.
4. Prioritization
- Critical: Core Architecture, Blockers, Database Schemas.
- High: Main Business Logic (Stub -> Impl).
- Medium: Edge cases, Error handling.
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.
- 4d ago First seen · 43 lines · 16 tokens per session scan A 279052257036
planning-decision-tree is a skill published in the GitHub repository MatrixFounder/Agentic-development (5 stars, last pushed yesterday), licensed Apache-2.0. It adds 16 tokens to every session and 426 once invoked, about $0.0001 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
Learn what defines effective BDD scenarios
Interactive guidance on writing complete, effective BDD scenarios for story-flow.
add-tests
Generates tests for existing code. Analyzes the target function, method, or class to identify the happy path, error cases, and edge cases, then writes test cases following the project's testing framework and naming conventions. Invoked when the user asks to add tests, write tests, cover code, or increase coverage.
tdd-implementation
Use when implementing any code change for a task – new behavior, a bugfix, or a revision after review – before writing the production code. Defines the failing-test-first cycle, public-seam testing, vertical slices, scaffold and infra handling, and counters to common excuses for tests-after-code.
test-writer
Writes tests that fail before a fix and pass after it.
test-generation
Generate and run unit/integration tests TDD-style across Python, Node, and .NET. Use when adding tests to untested code, implementing a feature test-first, or finding coverage gaps.
argent-tv-interact
Control and inspect TV apps via argent — Apple TV (tvOS), Android TV (leanback), and Amazon Fire TV (Vega). Boot the target, read focus, navigate with the D-pad remote, type, screenshot, and on Vega debug the JS runtime (evaluate, console logs, network inspector). Use when a task targets a TV (runtimeKind "tv", or…