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/agricidaniel/skill-forge/skill-forge-plannpx skills add AgriciDaniel/skill-forge --skill skill-forge-plangit clone --depth 1 https://github.com/AgriciDaniel/skill-forgeWrote 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/agricidaniel/skill-forge/skill-forge-plan)<a href="https://agentmods.dev/skills/agricidaniel/skill-forge/skill-forge-plan"><img src="https://agentmods.dev/badge/skills/agricidaniel/skill-forge/skill-forge-plan.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 | $0.00056 | $0.01345 |
| Opus 5 | $0.00028 | $0.00673 |
| Sonnet 5 | $0.00011 | $0.00269 |
| Haiku 4.5 | $0.00006 | $0.00135 |
Grade A, and why
skill-forge-plan 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.
How it starts
The opening of the file, as written. The whole thing — 213 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Architecture & Design Planning
Process
Step 1: Domain Discovery
Ask the user these questions (adapt based on context):
- What domain is this skill for? (e.g., SEO, advertising, DevOps, data analysis)
- What are the top 2-3 use cases? What should users be able to accomplish?
- What trigger phrases would users say? List 5-10 natural language triggers.
- Does it need external tools? MCP servers, APIs, CLI tools?
- Who is the target user? Developer, marketer, analyst, general user?
Step 2: Use Case Decomposition
For each use case, define:
Use Case: [Name]
Trigger: User says "[phrases]"
Steps:
1. [First action]
2. [Decision point or validation]
3. [Next action]
Result: [What success looks like]
Tools Needed: [built-in, MCP, scripts]
Step 3: Complexity Tier Assessment
Evaluate based on answers:
| Signal | Tier 1 | Tier 2 | Tier 3 | Tier 4 |
|---|---|---|---|---|
| Use cases | 1-2 | 2-3 | 4-8 | 8+ |
| Needs scripts? | No | Yes | Maybe | Yes |
| Sub-skills needed? | No | No | Yes | Yes |
| Parallel execution? | No | No | No | Yes |
| Reference docs? | No | Maybe | Yes | Yes |
| Industry templates? | No | No | Maybe | Yes |
Decision matrix:
- Single workflow, no scripts -> Tier 1 (minimal)
- Needs deterministic validation -> Tier 2 (workflow)
- Multiple distinct workflows -> Tier 3 (multi-skill)
- Complex domain with parallel delegation -> Tier 4 (ecosystem)
Step 4: Architecture Design
Based on tier, generate the architecture:
Tier 1 Output:
skill-name/
SKILL.md
Tier 2 Output:
skill-name/
SKILL.md
scripts/
validate.py
process.py
references/
domain-knowledge.md
Tier 3 Output:
skill-name/ # Main orchestrator
SKILL.md
references/
shared-reference.md
skills/
skill-name-sub1/
SKILL.md
skill-name-sub2/
SKILL.md
Tier 4 Output:
skill-name/ # Main orchestrator
SKILL.md
references/
ref1.md
ref2.md
scripts/
script1.py
script2.py
assets/
template1.md
template2.md
skills/
skill-name-sub1/
SKILL.md
skill-name-sub2/
SKILL.md
...
agents/
skill-name-role1.md
skill-name-role2.md
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 · 213 lines · 56 tokens per session scan A 31b1129349e7
skill-forge-plan is a skill published in the GitHub repository AgriciDaniel/skill-forge (166 stars, last pushed 4mo ago), licensed MIT. It adds 56 tokens to every session and 1,345 once invoked, about $0.0003 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 2026-08-30.
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