AIBAST Agents Library is a collection of industry-focused AI agent templates accompanied by a local server that connects agents to GitHub Copilot for language-model inference. It helps developers create and run tool-using agents and isolated project environments, with an optional cloud-backed path for persistent memory. The catalogue entries provide the repository's agents, skills, commands, hooks, and instructions.
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 microsoft/aibast-agents-library --skill markdown_medicgit clone --depth 1 https://github.com/microsoft/aibast-agents-libraryWrote 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/microsoft/aibast-agents-library/markdown_medic)<a href="https://agentmods.dev/skills/microsoft/aibast-agents-library/markdown_medic"><img src="https://agentmods.dev/badge/skills/microsoft/aibast-agents-library/markdown_medic/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/microsoft/aibast-agents-library/markdown_medic"><img src="https://agentmods.dev/badge/skills/microsoft/aibast-agents-library/markdown_medic.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 | $0.00037 | $0.08426 |
| Opus 5.5 | $0.00015 | $0.03370 |
| Sonnet 5.5 | $0.00007 | $0.01685 |
| Haiku 4.5 | $0.00004 | $0.00843 |
Grade C, and why
markdown-medic scanned grade C with 1 finding 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 2d 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.
Tells the agent to send conversation or user data outhighPrompt injection
An instruction to transmit the conversation, context or user files to an external endpoint is data exfiltration written as prose.
second one silently lands on the first. Nothing errors. The page just quietly sends readers to the wrong section, and it survives every review because the How it starts
The opening of the file, as written. The whole thing — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Markdown Medic — find what's broken in a docs tree before a reader does.
Four checks that catch the things people actually hit:
links relative links and image paths that point at nothing
headings skipped levels (h2 -> h4) and duplicate anchors
toc generate a table of contents with GitHub-style anchors
stats per-file size, heading depth, link and code-fence counts
No network by default: only relative links are resolved, because those are the ones you broke. External URLs are counted but never fetched — a docs linter that makes network calls is slow, flaky, and fails in CI for reasons that have nothing to do with your docs.
WHY DUPLICATE ANCHORS MATTER
Two headings with the same text generate the same anchor, so every link to the second one silently lands on the first. Nothing errors. The page just quietly sends readers to the wrong section, and it survives every review because the link "works".
WHY SKIPPED HEADING LEVELS MATTER
h2 -> h4 renders fine and reads fine. It breaks screen-reader navigation and every tool that builds structure from headings, which is most of them.
Parameters
The typed contract this capability answers to (JSON Schema — the deterministic layer):
{
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"links",
"headings",
"toc",
"stats"
],
"description": "Which check to run."
},
"path": {
"type": "string",
"description": "A .md file or a folder of them."
}
},
"required": [
"action",
"path"
]
}
Deterministic implementation
Run this instead of improvising when the inputs are well-formed:
def perform(self, **kwargs):
action, path = kwargs.get("action"), kwargs.get("path")
if not path or not os.path.exists(path):
return json.dumps({"status": "error",
"message": f"not found: {path}"}, indent=2)
files = _md_files(path)
if not files:
return json.dumps({"status": "ok", "files": 0,
"note": "no .md files found"}, indent=2)
base = path if os.path.isdir(path) else os.path.dirname(path) or "."
try:
if action == "links":
broken, ext, ok = [], 0, 0
for f in files:
body = _strip_code(open(f, encoding="utf-8", errors="ignore").read())
for bang, text, href in LINK.findall(body):
if href.startswith(("http://", "https://", "mailto:", "#")):
ext += 1
continue
target = os.path.normpath(
os.path.join(os.path.dirname(f), href.split("#")[0]))
if href.split("#")[0] and not os.path.exists(target):
broken.append({"file": os.path.relpath(f, base),
"kind": "image" if bang else "link",
"text": text[:40], "href": href})
else:
ok += 1
return json.dumps({
"status": "ok", "files": len(files), "broken": len(broken),
"relative_ok": ok, "external_not_checked": ext,
"findings": broken[:100],
"note": "External URLs are counted, never fetched — a linter "
"that makes network calls fails in CI for reasons "
"unrelated to your docs.",
}, indent=2)
if action == "headings":
issues = []
for f in files:
body = _strip_code(open(f, encoding="utf-8", errors="ignore").read())
hs = HEADING.findall(body)
seen, prev = {}, 0
for hashes, text in hs:
lvl = len(hashes)
if prev and lvl > prev + 1:
issues.append({"file": os.path.relpath(f, base),
"kind": "skipped-level",
"detail": f"h{prev} -> h{lvl}",
"heading": text[:50]})
a = _anchor(text)
if a in seen:
issues.append({"file": os.path.relpath(f, base),
"kind": "duplicate-anchor",
"detail": f"#{a}", "heading": text[:50]})
seen[a] = True
prev = lvl
return json.dumps({
"status": "ok", "files": len(files), "issues": len(issues),
"findings": issues[:100],
"note": "Duplicate anchors silently send every link to the "
"second heading to the first one instead.",
}, indent=2)
if action == "toc":
out = []
for f in files:
body = _strip_code(open(f, encoding="utf-8", errors="ignore").read())
lines = []
for hashes, text in HEADING.findall(body):
lvl = len(hashes)
if lvl == 1:
continue
clean = re.sub(r"`([^`]*)`", r"\1", text)
lines.append(" " * (lvl - 2) + f"- [{clean}](#{_anchor(text)})")
if lines:
out.append({"file": os.path.relpath(f, base),
"toc": "\n".join(lines)})
return json.dumps({"status": "ok", "files": len(out),
"tables_of_contents": out[:20]}, indent=2)
if action == "stats":
rows = []
for f in files:
raw = open(f, encoding="utf-8", errors="ignore").read()
body = _strip_code(raw)
hs = HEADING.findall(body)
rows.append({
"file": os.path.relpath(f, base),
"bytes": len(raw.encode()), "lines": raw.count("\n") + 1,
"headings": len(hs),
"max_depth": max([len(h) for h, _ in hs], default=0),
"links": len(LINK.findall(body)),
"code_fences": len(FENCE.findall(raw)) // 2,
})
rows.sort(key=lambda r: -r["bytes"])
return json.dumps({"status": "ok", "files": len(rows),
"total_bytes": sum(r["bytes"] for r in rows),
"documents": rows[:60]}, indent=2)
return json.dumps({"status": "error",
"message": f"unknown action {action!r}",
"valid": ["links", "headings", "toc", "stats"]}, indent=2)
except Exception as e:
return json.dumps({"status": "error",
"message": f"{type(e).__name__}: {e}"}, indent=2)
What ships with it
3 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.
- 2d ago First seen · 184 lines · 37 tokens per session scan C 960887aa2b6f
markdown-medic is a skill published in the GitHub repository microsoft/aibast-agents-library (8 stars, last pushed yesterday), licensed MIT. It adds 37 tokens to every session and 8,426 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it C with 1 finding (tells the agent to send conversation or user data out). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-11-06.
markdown-medic compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| markdown-medicmicrosoft/aibast-agents-library | Skill | 8 | yesterday | MIT | C | 37 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | yesterday | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 100k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 5d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |