Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/skillmds/skillmdnpx agentmods add skills/skillmds/skillmd/forter-agentic-readiness-auditWrote 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/skillmds/skillmd/forter-agentic-readiness-audit)<a href="https://agentmods.dev/skills/skillmds/skillmd/forter-agentic-readiness-audit"><img src="https://agentmods.dev/badge/skills/skillmds/skillmd/forter-agentic-readiness-audit/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/skillmds/skillmd/forter-agentic-readiness-audit"><img src="https://agentmods.dev/badge/skills/skillmds/skillmd/forter-agentic-readiness-audit.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 | $0.00105 | $0.04771 |
| Opus 5.5 | $0.00042 | $0.01908 |
| Sonnet 5 | $0.00021 | $0.00954 |
| Haiku 4.5 | $0.00011 | $0.00477 |
Grade A, and why
forter-agentic-readiness-audit scanned grade A 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 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
The probes shell out to `curl`, `jq`, and `python3`. If any is missing, surface the error to the user with the install command for their platform (`brew install jq`, `apt-get install jq python3`, etc.) and stop - don't c How it starts
The opening of the file, as written. The whole thing — 249 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Forter Agentic Readiness Audit
You score a website against the 25 guidelines in this repo. Each guideline has a machine-testable rubric in audit/m{M}-{N}.md (probe + weighted sub-checks + codebase hints). Your job: run the probes, score, prioritize, report.
Prerequisites
The probes shell out to curl, jq, and python3. If any is missing, surface the error to the user with the install command for their platform (brew install jq, apt-get install jq python3, etc.) and stop - don't continue with degraded probes.
Inputs
Ask the user for these if not provided:
- URL -
https://example.com. Required. - Local source path (optional but strongly recommended) - enables framework detection and per-file fix hints.
- Scope (optional) -
all,top N, or a comma-separated list of guideline IDs (m1-1,m4-1,m4-4). Default: all 25. - Output format(s) - markdown report (always), plus opt-in
score.jsonand PR-ready issue list.
If only a URL is given, run with codebase hints set to generic-only.
How the skill is wired
content/is the human-facing guide. Don't read it during scoring - it's prose. Surface its URLs in references and fixes only.audit/m{M}-{N}.mdis the source of truth for probes and scoring. Each file has frontmatter (complexity,impact,weight_total) and three sections:## Probe,## Rubric,## Codebase hints.audit/README.mddocuments the rubric format. Read it once if you're unfamiliar.
Process
1. Set up
Resolve and export shell variables once:
URL='<user URL>'
HOST=$(printf '%s' "$URL" | sed -E 's|^https?://([^/]+).*|\1|')
export HOST ORIGIN="https://$HOST"
mkdir -p ./report
If a source path was given, detect the framework once and cache the result:
REPO='<user path>'
# Detect: presence of files → framework label
# package.json + "next" → next.js (app router if app/ exists, else pages router)
# package.json + "express"|"fastify"|"@nestjs" → node-server
# Gemfile → rails
# requirements.txt|pyproject.toml + django|flask|fastapi → python-<framework>
# composer.json → php-<laravel|symfony|wordpress|custom>
# *.php in webroot, no composer.json → php-classic
# astro.config.* → astro · hugo.toml → hugo · config.yml + _posts → jekyll
# Implement the detection above, then:
echo "$FRAMEWORK" > ./report/framework
What ships with it
7 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.
- 4d ago First seen · 249 lines · 105 tokens per session scan A d00bba528f64
forter-agentic-readiness-audit is a skill published in the GitHub repository skillmds/skillmd (1 stars, last pushed yesterday), licensed MIT. It adds 105 tokens to every session and 4,771 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-19.
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