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/BagelHole/DevOps-Security-Agent-Skillsnpx agentmods add skills/bagelhole/devops-security-agent-skills/access-reviewWrote 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/bagelhole/devops-security-agent-skills/access-review)<a href="https://agentmods.dev/skills/bagelhole/devops-security-agent-skills/access-review"><img src="https://agentmods.dev/badge/skills/bagelhole/devops-security-agent-skills/access-review/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/bagelhole/devops-security-agent-skills/access-review"><img src="https://agentmods.dev/badge/skills/bagelhole/devops-security-agent-skills/access-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high Memory Poisoning · line 473 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
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 | $0.00025 | $0.04451 |
| Opus 5 | $0.00013 | $0.02226 |
| Sonnet 5 | $0.00005 | $0.00890 |
| Haiku 4.5 | $0.00003 | $0.00445 |
Grade A, and why
access-review 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 -s -H "Authorization: SSWS $OKTA_API_TOKEN" \ How it starts
The opening of the file, as written. The whole thing — 480 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Access Review
Implement periodic access review processes for AWS IAM, GitHub, Okta, and other identity providers, including automated reporting, certification workflows, and unused permission detection.
When to Use
- Conducting quarterly or annual access reviews for compliance (SOC 2, HIPAA, PCI DSS, ISO 27001)
- Identifying and removing stale accounts and unused credentials
- Certifying that current access levels match job responsibilities
- Detecting excessive privileges and dormant service accounts
- Generating evidence for auditor requests on access governance
Access Review Process
access_review_workflow:
1_scope:
actions:
- Define systems in scope for the review cycle
- Identify review owners (managers, system owners)
- Set review timeline and deadlines
- Generate access inventory from all identity sources
frequency:
privileged_access: Quarterly
standard_access: Semi-annually
service_accounts: Quarterly
api_keys: Monthly
2_extract:
actions:
- Pull current access data from all systems
- Correlate identities across platforms (SSO mapping)
- Enrich with last login and activity data
- Flag accounts for review (inactive, over-privileged, orphaned)
3_review:
actions:
- Assign review items to appropriate managers
- Manager certifies each user's access (approve/revoke/modify)
- Risk-based prioritization (privileged users reviewed first)
- Escalate non-responses after deadline
decisions:
approve: "Access is appropriate for current role"
modify: "Access needs adjustment (reduce/change scope)"
revoke: "Access is no longer needed"
4_remediate:
actions:
- Revoke access flagged for removal
- Modify access as directed by reviewers
- Document exceptions with justification
- Confirm changes with system owners
sla:
revocations: "Complete within 5 business days of decision"
modifications: "Complete within 10 business days"
exceptions: "Approved by security team, documented, time-limited"
5_report:
actions:
- Generate completion metrics (% reviewed, % on time)
- Document all decisions and actions taken
- Archive evidence for compliance audits
- Identify process improvements for next cycle
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 · 480 lines · 25 tokens per session scan A a558c7b37b79
access-review is a skill published in the GitHub repository BagelHole/DevOps-Security-Agent-Skills (1,067 stars, last pushed 3mo ago), licensed MIT. It adds 25 tokens to every session and 4,451 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 2026-08-30.
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