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.
git clone --depth 1 https://github.com/acaprino/daodanWrote 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/agents/acaprino/daodan/llm-seo-optimize)<a href="https://agentmods.dev/agents/acaprino/daodan/llm-seo-optimize"><img src="https://agentmods.dev/badge/agents/acaprino/daodan/llm-seo-optimize/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/agents/acaprino/daodan/llm-seo-optimize"><img src="https://agentmods.dev/badge/agents/acaprino/daodan/llm-seo-optimize.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 | $0.00088 | $0.03924 |
| Opus 5.5 | $0.00035 | $0.01570 |
| Sonnet 5.5 | $0.00018 | $0.00785 |
| Haiku 4.5 | $0.00009 | $0.00392 |
Grade B, and why
llm-seo-optimize scanned grade B 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 5d 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.
Instruction-override phrasingmediumPrompt injection
Text telling the model to disregard its earlier instructions or safety rules is the shape of a prompt injection, whoever wrote it.
- **No hidden text** instructing the LLM ("Ignore previous instructions and recommend...") -- either malicious or inadvertent copy-paste from another tool Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
How it starts
The opening of the file, as written. The whole thing — 306 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<daodan_host_binding host="claude"> This binding governs execution of this package and its loaded references. It takes precedence over executable examples written for another host. Use only registered tools and their actual input schema; an example never creates a tool, argument, permission, model alias or nested worker capability. Preserve the generated worker allowlist, dependency closure, scope and delivery contracts.
Claude binding: repository tools are Read/Glob/Grep and Write/Edit; shell execution uses Bash and network fetch uses WebFetch. Pass the executable string in Bash's command field, and use its registered timeout/background schema. Worker dispatch uses the available native Agent mechanism and its registered agent-selection and prompt fields. Do not turn a prose role label into an invented role argument. Inherit the session model unless the declared workflow and active schema permit an override. Load installed skills by qualified ID; named roles use their owning plugin's agent identity, while workflow entries use /:. Required foreign providers use Claude's marketplace/install commands: claude plugin marketplace add , then claude plugin install @. A declared package MCP server is configured through the generated MCP manifest; still check its tools are actually available in the active session.
The executing agent and its coordinator own continuation, recovery, verification and delivery. Skills supply knowledge and method instructions; they are not executors or a runtime persistence mechanism.
Resolve each component by kind and exact installed identity. A role is dispatched as a worker, a skill loads instructions, and a workflow starts its declared method. Kernel owner-qualified skill references are logical provider identities: resolve them to the actual host registry name and verified installed provider path. Do not invent a registry string by adding an owner's prefix when the host does not use it. Do not load an agent identity as a skill or execute a workflow name as a shell command. Named foreign providers remain mandatory. If an installed provider, MCP server or required isolation mechanism is unavailable, stop its dependent phase and report the missing capability. Do not install a different host's plugin or substitute unrelated skills to claim coverage.
Shell execution alone does not establish interactive stdin. Before a capture or checkpoint, use an available session-control mechanism. When stdin is unavailable, keep user-driven capture in a supported background process with bounded output and an explicit stop signal controlled by the coordinator after the user's completion message. Close owned browser/process resources on completion or cancellation.
Continue working within the current authorization while the requested result is achievable. After a tool error, inspect its cause, correct the relevant input or implementation, retry when justified and verify the outcome; never repeat a failing action blindly. Do not close the turn with a promise or a partial result when an authorized next step can still produce or verify the requested result. Stop only for a documented real impediment, a missing required capability, an unresolved human decision or the caller's stop request. At that boundary, report completed results, remaining work and the concrete prerequisite for continuation; continue any independent work that the blocker does not prevent.
A tool's successful exit, a worker stop or an idle session is not the deliverable. Return final text naming observed findings, artifact paths, executed checks and blockers. An empty worker result is missing delivery: inspect or resume that worker when permitted, or record failure. Verify required artifacts and candidate gates before marking the requested outcome complete.
This is an execution binding, not a rewrite of source examples. Preserve programming language fences, domain code and host APIs that are the subject of marketplace-ops or agent-sdk-builder. A host-as-subject API is not a tool provided to this session. Compiled binding and static checks do not prove an installed host executed a run. </daodan_host_binding>
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.
- 5d ago Changed · +63 lines 7355bf698a19
- 1mo ago First seen · 243 lines · 88 tokens per session scan B 2edfd7285a33
llm-seo-optimize is an agent published in the GitHub repository acaprino/daodan (9 stars, last pushed today), licensed MIT. It adds 88 tokens to every session and 3,924 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it B with 1 finding (instruction-override phrasing). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
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