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 skills add qarium/goga --skill goga-plan-by-designgit clone --depth 1 https://github.com/qarium/gogaWrote 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/qarium/goga/goga-plan-by-design)<a href="https://agentmods.dev/skills/qarium/goga/goga-plan-by-design"><img src="https://agentmods.dev/badge/skills/qarium/goga/goga-plan-by-design/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/qarium/goga/goga-plan-by-design"><img src="https://agentmods.dev/badge/skills/qarium/goga/goga-plan-by-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 10 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00017 | $0.03188 |
| Opus 5 | $0.00009 | $0.01594 |
| Sonnet 5 | $0.00003 | $0.00638 |
| Haiku 4.5 | $0.00002 | $0.00319 |
Grade A, and why
goga-plan-by-design 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 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.
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 — 344 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Planning Agent: Design Document → ralphex Plan
Purpose
Compiles a finalized architectural decision from a design document into a ralphex-compatible execution plan — a structured markdown file that ralphex can autonomously execute through Claude Code. You decompose a finalized architectural decision into coding tasks.
Phase 1: Context Loading
Step 1: Load DSL Specification
Use the Skill tool to invoke goga-cell.
Use for:
- Understanding DSL terminology when compiling the design document into tasks
Step 2: Load DSL Application Principles
Use the Skill tool to invoke goga-cookbook.
Use for:
- Understanding Entity vs Routine when compiling entities into tasks
- Principles for working with
.usages/when planning tasks for creating/updating usage files
Step 3: Load Language Implementation Rules
Use the Skill tool to invoke goga-lang-disp.
The language skill defines implementation conventions: cell structure, facade, signature rules, naming. Examples in other skills (DSL, cookbook, templates) may use naming from one language (e.g., snake_case) while the target language requires another (e.g., PascalCase) — the language skill contains authoritative rules for the target language. Apply them when compiling the plan.
Step 4: Load Plan Template
Read the file output-template.md from the current skill.
Use for:
- Plan structure (sections, headings, checkboxes)
- Templates for three task types (infrastructure, TDD coding, integration tests)
- Format for "Validation Commands" and "Completion Criteria" sections
Step 5: Load Project Conventions
Read the file conventions.md from the current skill.
Use for:
- Implementation rules (internal cell structure, public surface, naming)
- Traceability rules and contract-to-test mapping
- Test classification (contract, logic, integration)
Step 6: Load Design Document
Read the file from the path printed by goga history path -f design.md.
If the design document does not exist — stop and ask the user to run /goga:design first.
What ships with it
2 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 Changed · -1 lines f1bacdf8ec43
- 7d ago First seen · 345 lines · 17 tokens per session scan A bb601877a5b3
goga-plan-by-design is a skill published in the GitHub repository qarium/goga (25 stars, last pushed 3d ago), licensed BSD-3-Clause. It adds 17 tokens to every session and 3,188 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 2026-09-03.
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