Borrowing it
Nothing to install: this file belongs to ASISaga/linkedin.asisaga.com. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ASISaga/linkedin.asisaga.com/main/.github/skills/repository-onboarding/SKILL.mdgit clone --depth 1 https://github.com/ASISaga/linkedin.asisaga.comWrote 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/asisaga/linkedin.asisaga.com/repository-onboarding)<a href="https://agentmods.dev/skills/asisaga/linkedin.asisaga.com/repository-onboarding"><img src="https://agentmods.dev/badge/skills/asisaga/linkedin.asisaga.com/repository-onboarding/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/asisaga/linkedin.asisaga.com/repository-onboarding"><img src="https://agentmods.dev/badge/skills/asisaga/linkedin.asisaga.com/repository-onboarding.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00018 | $0.00545 |
| Opus 5 | $0.00009 | $0.00272 |
| Sonnet 5 | $0.00004 | $0.00109 |
| Haiku 4.5 | $0.00002 | $0.00055 |
Grade A, and why
repository-onboarding 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 8d 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repository Onboarding Skill
Role: Bootstrap Specialist for Agent Intelligence Systems
Automated setup of complete GitHub Copilot agent intelligence system in new repositories based on templates and specifications.
When to Use This Skill
Use this skill when:
- Setting up a new repository from scratch
- Adding agent intelligence to existing repository
- Migrating manual workflows to automated systems
- Standardizing repository structure across projects
Core Principles
- Template-Based: Use proven templates from specifications
- Technology-Aware: Adapt to repository's tech stack
- Minimal Manual Work: Automate as much as possible
- Validation First: Ensure everything works before completion
Workflows
Workflow 1: New Repository Setup
Purpose: Bootstrap complete system in empty repository
Steps:
- Create directory structure
- Generate copilot-instructions.md from template
- Create instruction files based on tech stack
- Set up agents/prompts/skills
- Create specs/docs
- Configure validation
- Verify setup
Workflow 2: Existing Repository Enhancement
Purpose: Add agent intelligence to existing repository
Steps:
- Backup existing .github/
- Analyze existing structure
- Integrate agent system
- Migrate existing patterns
- Validate integration
Tool Integration
Directory creation:
mkdir -p .github/{instructions,specs,docs,agents,prompts,skills}
Validation:
./.github/skills/repository-onboarding/scripts/validate-setup.sh
References
→ Agent spec: .github/specs/agents.md — Agent file format and conventions
→ Prompt spec: .github/specs/prompts.md — Prompt file format and conventions
→ Skill spec: .github/specs/skills.md — Skill file format and conventions
→ Instructions spec: .github/specs/instructions.md — Instruction file format and conventions
→ Framework spec: .github/specs/agent-intelligence-framework.md — Framework spec
→ Onboarding prompt: .github/prompts/repository-onboarding.prompt.md — Onboarding prompt
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.
- 8d ago First seen · 80 lines · 18 tokens per session scan A 59740780c8f6
repository-onboarding is a skill published in the GitHub repository ASISaga/linkedin.asisaga.com (0 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 18 tokens to every session and 545 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.
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