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 adriannoes/awesome-agentic-ai --skill hunt-miscgit clone --depth 1 https://github.com/adriannoes/awesome-agentic-aiWrote 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/adriannoes/awesome-agentic-ai/hunt-misc)<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/hunt-misc"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/hunt-misc/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/adriannoes/awesome-agentic-ai/hunt-misc"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/hunt-misc.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 107 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 133 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 137 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Excessive Agency · line 169 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 194 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00028 | $0.03786 |
| Opus 5 | $0.00014 | $0.01893 |
| Sonnet 5 | $0.00006 | $0.00757 |
| Haiku 4.5 | $0.00003 | $0.00379 |
Grade A, and why
hunt-misc 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 9d 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.
curl -v "https://target.com/path" \ How it starts
The opening of the file, as written. The whole thing — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Crown Jewel Targets
Why this vuln class pays: MISC vulnerabilities span access control failures, information disclosure, session/auth logic bugs, and misconfiguration — the categories that consistently produce the highest payouts because they map directly to business impact: data exposure, account takeover, privilege escalation, and infrastructure compromise.
Highest-value targets:
- SaaS platforms with role hierarchies (Shopify, GitHub, GitLab) — any boundary between owner/admin/staff/guest is a privilege escalation surface
- Identity/auth flows — invitation links, password reset, SAML SSO, OAuth token scopes
- Multi-tenant systems — one tenant touching another tenant's data
- Internal APIs — LFS endpoints, pre-receive hooks, internal GraphQL/REST that assume caller is trusted
- Domain/DNS management features — transfer controls, subdomain delegation
- Token/credential management — PAT scopes, deploy keys, API tokens stored in config fields
Asset types that pay most:
- Core product APIs (not marketing subdomains)
- Enterprise/self-hosted editions (GitHub Enterprise, GitLab EE)
- Partner/collaborator invitation systems
- OAuth app integrations and webhook endpoints
Attack Surface Signals
URL patterns to watch:
/admin/*/transfer
/invitations/*
/partners/*/accept
/api/v*/repos/*/lfs/*
/-/settings/integrations/sentry
/api/v*/user/installations
/hooks/pre-receive/*
/reset-password?token=
/auth/saml/callback
/api/v*/packages/pypi/*
Response header signals:
X-Request-Id (pitchfork/Rack — check for header injection)
X-Shopify-Shop-Api-Call-Limit
X-GitLab-*
JS patterns revealing internal surfaces:
// Look for hardcoded internal API paths
fetch('/internal/api/
graphql { installations(
"scope": [], // empty scopes on tokens
"permissions": {"contents": "read"} // minimal scope PATs
Tech stack signals:
- Ruby/Rack middleware (CRLF injection risk in
pitchfork) - SAML SSO enabled on enterprise instances
- PyPI proxy/mirror configurations (dependency confusion)
- Sentry error tracking integration fields (SSRF/token leak vector)
- Multi-role invitation systems (partners, staff, collaborators)
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.
- 9d ago First seen · 270 lines · 28 tokens per session scan A 69cdecd21056
hunt-misc is a skill published in the GitHub repository adriannoes/awesome-agentic-ai (57 stars, last pushed 14d ago), licensed MIT. It adds 28 tokens to every session and 3,786 once invoked, about $0.0001 per session on Opus 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 2026-09-03.
Other skills, from other repositories
importing-a-codebase
Use when the repo holds real source code but no specs: the existing-codebase branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for empty workspaces (starting-a-new-project) or feature work in a specced project (brainstorming).
starting-a-new-project
Use when the workspace is empty — no code yet — and the user brings a raw idea: the brand-new branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for features in an existing project — use brainstorming instead.
todos
This chat has a shared, live TODO plan — your tasks for the conversation, which the user also edits. Read this skill and reach for the todo tools whenever a request takes more than a couple of steps. It covers the plan model (group = task, items = its steps; loose items are the user's lane), how to work it: propose…
writing-workflow-skills
Use when adding a new workflow skill to pi-thinkrail-workflow, changing an existing workflow skill's role, trigger, handoff, or structure, or checking a workflow skill against the workflow system's rules. Not for authoring general-purpose skills outside this package.
brainstorming
Use this BEFORE any creative or feature work: building a new feature, adding functionality, changing behavior, or making a nontrivial design decision. Turns the user's request into a validated design — recorded as a spec-graph task-spec — before any implementation. Do not skip this because a change looks small.
reviewing-changes
Use when a review package asks you to review a plan step's change set (todo.startReview): you are the REVIEWER, not the author. How to judge an agent-written diff, file findings with addreviewcomment, and settle with exactly one reviewverdict.