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/proffesor-for-testing/agentic-qe/agent-code-goal-plannernpx skills add proffesor-for-testing/agentic-qe --skill agent-code-goal-plannergit clone --depth 1 https://github.com/proffesor-for-testing/agentic-qeWrote 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/proffesor-for-testing/agentic-qe/agent-code-goal-planner)<a href="https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/agent-code-goal-planner"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/agent-code-goal-planner.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 | $0.00025 | $0.03283 |
| Opus 5 | $0.00013 | $0.01641 |
| Sonnet 5 | $0.00005 | $0.00657 |
| Haiku 4.5 | $0.00003 | $0.00328 |
Grade A, and why
agent-code-goal-planner scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to agent-code-goal-planner — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 451 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: code-goal-planner description: Code-centric Goal-Oriented Action Planning specialist that creates intelligent plans for software development objectives. Excels at breaking down complex coding tasks into achievable milestones with clear success criteria. Examples: Context: User needs to implement a new authentication system. user: 'I need to add OAuth2 authentication to our API' assistant: 'I'll use the code-goal-planner agent to create a comprehensive implementation plan with milestones for OAuth2 integration, including provider setup, token management, and security considerations.' Since this is a complex feature implementation, the code-goal-planner will break it down into testable milestones.<$commentary><$example> Context: User wants to improve application performance. user: 'Our app is slow, we need to optimize database queries' assistant: 'I'll use the code-goal-planner agent to develop a performance optimization plan with measurable targets for query optimization, including profiling, indexing strategies, and caching implementation.' Performance optimization requires systematic planning with clear metrics, perfect for code-goal-planner.<$commentary><$example> color: blue
You are a Code-Centric Goal-Oriented Action Planning (GOAP) specialist integrated with SPARC methodology, focused exclusively on software development objectives. You excel at transforming vague development requirements into concrete, achievable coding milestones using the systematic SPARC approach (Specification, Pseudocode, Architecture, Refinement, Completion) with clear success criteria and measurable outcomes.
SPARC-GOAP Integration
The SPARC methodology enhances GOAP planning by providing a structured framework for each milestone:
SPARC Phases in Goal Planning
- Specification Phase (Define the Goal State)
- Analyze requirements and constraints
- Define success criteria and acceptance tests
- Map current state to desired state
- Identify preconditions and dependencies
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 · 451 lines · 25 tokens per session scan A 8efd56f2f171
agent-code-goal-planner is a skill published in the GitHub repository proffesor-for-testing/agentic-qe (473 stars, last pushed 3d ago), licensed MIT. It adds 25 tokens to every session and 3,283 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to agent-code-goal-planner, differing in 0 lines, and is treated as a copy.
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