skill-forge
Skill6 starsChanged 3 months agoMITView on GitHub
Meta-skill and design compass for creating new skills and upgrading existing ones with a deliberate push toward being maximally technological, creative, and aesthetically disciplined. Use when the user wants to create a skill from scratch, reshape an existing skill, make a skill more reliable/technological, more creative/varied, or more visually polished — or when a skill feels templated, generic, or mechanically weak. Trigger on phrases like "создай скил", "новый скил", "улучши скил", "сделай скил креативнее", "эстетичный скил", "технологичный скил", "скилл выглядит шаблонно", "перепиши SKILL.md", even if the user does not say the word "skill" explicitly. Also use when reviewing a skill before release.
49 other projects use a version of this.
Adopted by
Most recently taken up by
- brebuilds/claude-skillstheir own version, first seen Nov 8, 2026
- gxh98/haoge-skill-forgetheir own version, first seen Nov 8, 2026
- yashaswi-khurana/Skillstheir own version, first seen Nov 8, 2026
- Arcanea-Labs/Starlight-Intelligence-Systemtheir own version, first seen Nov 8, 2026
- AthenDrakomin-hub/agent-skillstheir own version, first seen Nov 1, 2026
- ligj1706/ProSkillstheir own version, first seen Nov 1, 2026
Used with
Projects with it also use sigma, agent-forge and 2 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
sanyuan0704Skillsigma
Personalized 1-on-1 AI tutor using Bloom's 2-Sigma mastery learning. Guides users through any topic with Socratic questioning, adaptive pacing, and rich visual output (HTML dashboards, Excalidraw concept maps, generated images). Use when user wants to learn something, study a topic, understand a concept, requests tutoring, says 'teach me', 'I want to learn', 'explain X to me step by step', 'help me understand', or invokes /sigma. Triggers on: learn, study, teach, tutor, understand, master, explain step by step.
Also in 3 projects that use this
xyreinsurance119Skillagent-forge
Создание, улучшение и аудит скиллов и агентов OpenClaw. Три режима: создание скилла (11 шагов), создание агента (9 шагов, с памятью и автоулучшением), улучшение существующего (5 шагов). Triggers: 'создай скилл', 'новый скилл', 'создай агента', 'новый агент', 'улучши скилл', 'skill creator', 'agent creator', 'скиллмейкер'.
Also in 3 projects that use this
localSummerSkillskill-review
回顾当前对话,整理 skill 使用情况、代码质量反馈和迭代建议,生成待确认的更新清单
Also in 3 projects that use this
NVIDIASkilldeep-research
Queue deep, multi-step research and analysis tasks to the DeepAgents worker. Supports execution depth presets, request-specific rubrics, SubAgent delegation, and RubricMiddleware cross-validation.
Also in 3 projects that use this
Other versions49 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 49
- sanyuan0704/code-review-expert★ 3.9ksame name
- sanyuan0704/sanyuan-skills★ 3.9ksame name
- AgriciDaniel/skill-forge★ 166same name
- svy04/ballast★ 73same name
- danilokhury/Synabun★ 70same name
- motiful/skill-forge★ 45same name
- WilliamSaysX/skill-forge★ 43same name
- bjcoombs/ai-native-toolkit★ 32same name
- GodModeAI2025/skill-forge★ 18same name
- maroffo/claude-forge★ 17same name
39 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository59 other files it gives its agents.
- skills/chronos/references/AGENTS.mdAGENTS.md
- api-contract-testingSkill
- api-doc-generatorSkill
- canonSkill
- censorSkill
- changelog-generatorSkill
- chronosSkill
- code-reviewSkill
- commit-lintSkill
- commit-message-writerSkill
- coverage-analyzerSkill
- csv-proSkill
- data-analysisSkill
- deweySkill
- diagram-makerSkill
- doc-compareSkill
- docs-productSkill
- docs-projectSkill
- docs-systemSkill
- dsh-runnerSkill
- frontend-a11ySkill
- frontend-design-tasteSkill
- frontend-perfectionSkill
- frontend-performanceSkill
- frontend-testingSkill
- github-repo-hygieneSkill
- long-running-agent-workflowSkill
- mermaid-to-imageSkill
- mobile-frontendSkill
- pdf-report-builderSkill
- plan-skillSkill
- prd-to-appSkill
- presentation-craftSkill
- presentation-engineeringSkill
- presentation-makerSkill
- raster-to-svgSkill
- reddit-karmaSkill
- repo-community-filesSkill
- repo-metadata-healthSkill
- repo-readme-assetsSkill
- repo-social-previewSkill
- secret-scannerSkill
- security-reviewSkill
- seo-auditSkill
- seo-contentSkill
- seo-crawlSkill
- seo-schemaSkill
- seo-toolkitSkill
- skill-feedbackSkill
- skill-suggesterSkill
- sql-helperSkill
- systematic-debuggerSkill
- test-generatorSkill
- test-graphicsSkill
- velesSkill
- version-bumperSkill
- video-script-writerSkill
- web-replicationSkill
- web-scraperSkill
The file
We split this skill into the rules it gives an agent
6 rules. 0 are common, 4 are distinctive, and 2 are very specific to this project.
0
Common
Most of the 42 edited versions we read keep these.
4
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 33
Progressive disclosure: keep SKILL.md under 500 lines.
- Distinctive: line 37
Voice: write in the imperative. Explain the *why* instead of heaped MUST/ ALWAYS/NEVER — all-caps rigidity is a yellow flag.
- Distinctive: line 38
ALWAYS/NEVER — all-caps rigidity is a yellow flag.
- Distinctive: line 40
Principle of Lack of Surprise: no malware, no deceptive or malicious content.
- Very specific: line 74
Binary-format safety: when generating OOXML/PDF, follow the hard rules — no #/8-digit hex (corrupts files), parse with defusedxml …
- Distinctive: line 155
Do not use to perform the domain task itself.
“Common” is measured: kept by at least 6 in 10 of the 42 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
skill-forge
A compass, not a dictator. This skill helps you design skills that are maximally technological (engineered, reliable, composable), creative (generative, varied, distinctive), and aesthetically disciplined (intentional, not templated). It separates the obligatory base — rules you must not break — from accents — amplifiers you choose per task.
Russian triggers:
создай скил,новый скил,улучши скил,сделай скил креативнее,эстетичный скил,технологичный скил,скилл шаблонный,перепиши SKILL.md,мета-скилл,проверь скилл перед релизом.
Level 0 — Hard rules (the base, never break these)
These come from the official Agent Skills specification (agentskills.io) plus our own working gates. They are non-negotiable.
- Frontmatter:
name(≤64 chars,a-z 0-9 -, no double hyphens, MUST match the folder name) anddescription(≤1024 chars, MUST state what the skill does AND when to use it). Put all "when to use" info indescription, never in the body. Make triggers a little "pushy" to fight undertriggering — list synonyms and casual phrasings. - Progressive disclosure: keep
SKILL.mdunder 500 lines. Bundle code inscripts/(deterministic, repetitive tasks), docs inreferences/(loaded as needed; add a TOC if >300 lines), outputs inassets/. Reference files one level deep only. - Voice: write in the imperative. Explain the why instead of heaped MUST/ ALWAYS/NEVER — all-caps rigidity is a yellow flag. The model is smart; reason with it.
- Principle of Lack of Surprise: no malware, no deceptive or malicious content. A skill's intent must match its description.
- Single data contract: one spec file (e.g.
deck.json) is the source of truth; every stage reads/writes it so artifacts are regenerable. - Mandatory gates: nothing is "done" until automated checks PASS. At minimum: structural/format validation, content QA, and — for any visual output — a real-browser or render gate. Require EVIDENCE, not assertion: the skill must show the command it ran, its output, and the exit status. Use SCOPED CLAIMS — separate failures the change caused from pre-existing ones ("3 pre-existing failures, my change introduced none"). For unattended runs, back the gate with a deterministic Stop hook or a /goal evaluator so a turn cannot end on a false "done".
- Reproducibility: deterministic seed so the same input yields the same output on another day.
- Anti-template baseline (our enforcement, mechanical): ≤2 typefaces, ≤4
accent roles (keep 60-30-10), WCAG contrast (text ≥4.5:1, large/non-text
≥3:1), zero raw hex outside
:root(every color is a token), one mood per artifact, one idea per slide, assertion headlines (full sentence with a verb), words-per-slide budget.
Level 1 — Accent: Technological
Pick this when the skill must be engineered. It is an amplifier, not required.
- Modular base + pluggable patterns — never a monolithic template. Each artifact assembles from base + only the patterns it uses, so no two outputs share a prebuilt shell.
- Composable pipeline: small single-purpose scripts, one command per stage, everything inspectable and debuggable.
- Real verification: for any UI/visual output, a Playwright/Chromium gate is mandatory (geometry, overflow, clipping, keyboard nav).
- Fixed contract constants (lesson from the official
pptxskill): pin the canvas (e.g. 1600×900), the safe font (e.g. Arial — LibreOffice substitutes matter), and exempt decorative elements from bounds checks by naming convention (ghost*,decor*,chrome-*). - Binary-format safety: when generating OOXML/PDF, follow the hard rules —
no
#/8-digit hex (corrupts files), parse withdefusedxml(round-tripping throughElementTreerewrites namespaces and corrupts), run the validator after generating and fix in the generator, never hand-edit packed XML.
Level 2 — Accent: Creative
Pick this when the skill must vary and surprise (in a good way).
- Generative composition from a seed: synthesize layout/parameters deterministically from a deck seed (title + date + index) so rebuilding on another day yields a different but reproducible mix.
- Variety across artifacts: different outputs should carry different visual "handwriting" — not one shared base. Multiple base styles, each deck picks its own.
- Signature element: one memorable, brief-true motif per artifact (NOT a color bar or accent stripe — those read as AI filler).
- Avoid the three AI-default looks: (1) cream
#F4F1EA+ high-contrast serif- terracotta; (2) near-black + single acid-green/vermilion accent; (3) broadsheet hairline rules, zero radius, newspaper columns. Where the brief leaves an axis free, don't spend that freedom on a default.
Level 3 — Accent: Aesthetic
Pick this when the skill must look intentional.
- Mood system:
swiss | editorial | flat | glass | darkdrives the regime; one mood per artifact, one radius/stroke language. - Token system (4 parts): palette as 4–6 named hex; type as 2+ roles (characterful display used with restraint + complementary body + utility face); layout as one-sentence prose + ASCII wireframes; signature as the single unique element.
- Assertion headlines: full sentences with a verb — a conclusion, not a topic.
- Typography floor: body text readable at projection scale (≥17px cards, labels ≥17px, metric values 30–48px); re-check overflow after any font change.
- Restraint: spend your boldness in one place — let the signature be the one memorable thing, keep everything else quiet. Chanel's rule: before shipping, remove one accessory. Match complexity to the vision; elegance is executing the chosen vision well.
- Structural honesty: numbering/eyebrows/dividers should encode something true about the content, not decorate it (numbered markers only if it's actually a sequence).
Process — the build loop
Adapted from the official skill-creator flow, with an accent pass added:
- Capture intent — what should the skill enable? when should it trigger? what's the output format? do we need test cases (objective outputs do; subjective ones often don't)?
- Draft SKILL.md — follow Level 0; choose accents from Levels 1–3 that fit the task.
- Test prompts — 2–3 realistic user phrasings; save to
evals/evals.json. - Parallel runs — with-skill vs baseline subagents in the same turn; capture
total_tokens/duration_mstotiming.json(only chance to get them). - Grade — objective assertions with
text/passed/evidence, no partial credit; superficial pass = fail. Subjective quality → human judgment. - Accent pass (added) — on each iteration ask: did we keep it technological, creative, and aesthetically disciplined? Did it slip into a default look or a monolith?
- Improve — generalize from feedback; keep the prompt lean; explain the why;
if all test runs wrote the same helper, bundle it into
scripts/. - Optimize description — generate ~20 trigger queries (mix should/should-not,
include near-misses and casual typos), split 60/40 train/test, iterate up to 5×
to get
best_descriptionby test score. - Package —
package_skill→.skillfile; preserve the originalname.
Release checklist
- Level 0 hard rules all satisfied (frontmatter, <500 lines, gates green)?
- Chosen accents actually amplified, not just "it works"?
- Escaped the three AI-default looks (Level 2)?
- Token system coherent: one mood, ≤2 typefaces, ≤4 accent roles, zero raw hex?
- Signature element present and brief-true (not a stripe/bar)?
- Description triggers reliably, including casual/near-miss phrasings?
A skill that passes Level 0 and at least one accent is shippable. A skill that passes all three accents is exceptional.
Boundaries
- Do not use to perform the domain task itself; it designs or upgrades skills.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

