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 sseshachala/conductai --skill conduct-guardgit clone --depth 1 https://github.com/sseshachala/conductaiWrote 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/sseshachala/conductai/conduct-guard)<a href="https://agentmods.dev/skills/sseshachala/conductai/conduct-guard"><img src="https://agentmods.dev/badge/skills/sseshachala/conductai/conduct-guard/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/sseshachala/conductai/conduct-guard"><img src="https://agentmods.dev/badge/skills/sseshachala/conductai/conduct-guard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00047 | $0.00250 |
| Opus 5 | $0.00023 | $0.00125 |
| Sonnet 5 | $0.00009 | $0.00050 |
| Haiku 4.5 | $0.00005 | $0.00025 |
Grade A, and why
conduct-guard 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 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.
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
What ConductGuard does
ConductGuard runs as an MCP server (conductguard-mcp) that intercepts tool calls from Claude Code before they execute. It checks each call against the policies your team lead configured in the Conduct Guard dashboard.
- Blocked calls are rejected with an explanation
- All calls (allowed and blocked) are logged to Guard Insights
- Coverage dashboard shows which developers have Guard wired
Setup
pip install conduct-cli
conduct whoami # verify workspace is set
conductguard-mcp # starts automatically via .mcp.json
Key CLI commands
conduct switch <name> # switch workspace + re-sync Guard policies
conduct guard status # show hook wiring, policy count, last sync
conduct whoami # workspace + Guard + Booster status at a glance
Guard Insights
View the events feed and developer coverage at /guard/insights in the Conduct console.
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 · 33 lines · 47 tokens per session scan A 82f03b86df0e
conduct-guard is a skill published in the GitHub repository sseshachala/conductai (32 stars, last pushed today), licensed Apache-2.0. It adds 47 tokens to every session and 250 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.
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