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/sandbaseai/sandbase-skills/github-profile-researchnpx skills add sandbaseai/sandbase-skills --skill github-profile-researchgit clone --depth 1 https://github.com/sandbaseai/sandbase-skillsWrote 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/sandbaseai/sandbase-skills/github-profile-research)<a href="https://agentmods.dev/skills/sandbaseai/sandbase-skills/github-profile-research"><img src="https://agentmods.dev/badge/skills/sandbaseai/sandbase-skills/github-profile-research.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 5.1 | $0.00042 | $0.00320 |
| Opus 5 | $0.00021 | $0.00160 |
| Sonnet 5 | $0.00008 | $0.00064 |
| Haiku 4.5 | $0.00004 | $0.00032 |
Grade A, and why
github-profile-research 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.
What it actually says
GitHub Profile Research
Research GitHub user profiles including repositories, contributions, languages, stars, and activity patterns. Useful for developer talent sourcing, open-source community research, and technical due diligence on engineering teams. Read the API map before selecting a capability.
Call SandBase capabilities
For every selected tool, call sandbase_describe_tool first and use only arguments in its current input schema. Then call sandbase_call_tool with the exact tool_name.
Available Tools
strale_github_user_profile
Workflow
- Understand the user's research question, target, and context.
- Call
sandbase_describe_toolfor each selected tool to confirm parameter schema. - Call
sandbase_call_toolwith the exact tool_name and schema-defined arguments. - Synthesize findings into a clear, evidence-backed answer.
- Cite sources, note evidence gaps, and separate observations from interpretations.
Guidelines
- Always call
sandbase_describe_toolbefore using any capability. - Cite sources and preserve attribution (URLs, usernames, dates, metrics).
- Separate factual observations from analysis and recommendations.
- If data is unavailable, note the gap and continue with available evidence.
- Read-only research only. Never take actions on platforms.
What ships with it
1 file 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.
- 5d ago First seen · 33 lines · 42 tokens per session scan A 477628167fbc
github-profile-research is a skill published in the GitHub repository sandbaseai/sandbase-skills (122 stars, last pushed 2d ago), licensed Apache-2.0. It adds 42 tokens to every session and 320 once invoked, about $0.0002 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.
Other skills, from other repositories
skill
Ten native DSH tools give a text-only agent eyes. Use these structured tools directly; do not shell out to the bundled Python scripts or reproduce their implementation. Vision API credentials and model settings are managed by the plugin, so tool calls do not receive credentials.
audit
Use when asked to audit a codebase, or when the /audit command runs — find security, correctness, and quality issues across a project and report them organized by severity.
vuln-check
Use when asked to check for security vulnerabilities, or when the /vuln-check command runs — scan the project for known vulnerable dependencies and security anti-patterns.
pr-comments
Use when the user asks to review pull request comments, or when the /pr-comments command runs — fetch and analyze PR review comments on the current branch and summarize actionable items.
release-notes
Use when asked to generate release notes, or when the /release-notes command runs — derive user-facing release notes from the change history since the last release.
review
Use when asked to review a codebase or a change, or when the /review command runs — assess design, correctness, maintainability, and test coverage with actionable feedback.