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 RedHatProductSecurity/prodsec-skills --skill agent-identitygit clone --depth 1 https://github.com/RedHatProductSecurity/prodsec-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/redhatproductsecurity/prodsec-skills/agent-identity)<a href="https://agentmods.dev/skills/redhatproductsecurity/prodsec-skills/agent-identity"><img src="https://agentmods.dev/badge/skills/redhatproductsecurity/prodsec-skills/agent-identity/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/redhatproductsecurity/prodsec-skills/agent-identity"><img src="https://agentmods.dev/badge/skills/redhatproductsecurity/prodsec-skills/agent-identity.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 | $0.00038 | $0.00447 |
| Opus 5 | $0.00019 | $0.00224 |
| Sonnet 5 | $0.00008 | $0.00089 |
| Haiku 4.5 | $0.00004 | $0.00045 |
Grade A, and why
agent-identity 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 10d 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
Agent Own Identity
Security Recommendation
Agents SHOULD have their own identity and SHOULD NOT use the identity of a human user. Each agent must be a distinct, identifiable entity in the system.
Rationale
Giving agents their own identity enables:
- Specific permissions: Assign permissions tailored to the agent's purpose, following least privilege
- Audit trail: Distinguish agent actions from human actions in logs and audit records
- Runtime identification: Identify which agent performed which action at runtime
- Accountability: Trace decisions and actions back to the specific agent
- Blast radius control: Limit the impact of a compromised agent to its own permissions
Using Human Identity (Anti-Pattern)
When an agent acts under a human user's identity:
- All agent actions appear as user actions in audit logs
- The agent inherits all of the user's permissions (likely more than needed)
- It becomes impossible to distinguish human from agent activity
- Revoking agent access requires revoking the user's credentials
Implementation Guidance
- Register each agent as a distinct service account or workload in the identity provider
- Use SPIFFE IDs or service account identifiers for agent identity
- Assign agent-specific scopes and permissions (not inherited from users)
- Include agent identity in all log entries and audit records
- When an agent acts on behalf of a user, use delegation mechanisms (e.g., Token Exchange with
actclaim) that preserve both identities
Example: Agent vs. User in Audit Log
{
"action": "tool:execute",
"tool": "database-query",
"actor": {
"type": "agent",
"id": "agent:data-analyst-v2",
"delegated_by": "user:jane.doe"
},
"timestamp": "2026-03-03T10:15:00Z"
}
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.
- 10d ago First seen · 54 lines · 38 tokens per session scan A 3c2fc7257ca8
agent-identity is a skill published in the GitHub repository RedHatProductSecurity/prodsec-skills (52 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 38 tokens to every session and 447 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
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…