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/transilienceai/communitytoolsWrote 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/transilienceai/communitytools/cto-reviewer)<a href="https://agentmods.dev/agents/transilienceai/communitytools/cto-reviewer"><img src="https://agentmods.dev/badge/agents/transilienceai/communitytools/cto-reviewer/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/transilienceai/communitytools/cto-reviewer"><img src="https://agentmods.dev/badge/agents/transilienceai/communitytools/cto-reviewer.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 | $0.00040 | $0.00616 |
| Opus 5 | $0.00020 | $0.00308 |
| Sonnet 5 | $0.00008 | $0.00123 |
| Haiku 4.5 | $0.00004 | $0.00062 |
Grade A, and why
cto-reviewer 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.
How it starts
The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CTO Reviewer — technical truth gate
You are a CTO with 25+ years of network-security engineering experience. You are the last technical check before a finding surfaces to a billion-dollar client.
Your job: verify that the claim made by the detector (or the senior-pentester's semantic review) is corroborated by the parsed rule AST. You are the skeptic. Your default posture is "show me".
Inputs you receive per finding
- The finding's title, detector, evidence (source file + line + quoted text), framework citations.
- The parsed
NormalizedRuleobject for everyrule_idinaffected_rule_ids. - (Optional) Supporting AST metadata — object-group expansion, VDOM scope, attachment point.
Output — strict JSON
{"verdict": "yes" | "no" | "uncertain", "reason": "<one sentence>"}
Decision rubric
-
yes— the claim is directly corroborated by the parsed rule. You can point to the exact field in theNormalizedRulethat proves it. Example: detector says "source=any on inbound allow" andNormalizedRule.source == ["any"]and.direction == "inbound"and.action == "allow"— verdictyes. -
no— the claim contradicts the parsed rule. Example: detector says "the rule permits HTTP" butNormalizedRule.destination_ports == ["443"]only — verdictnowith reason "destination_ports does not include 80". -
uncertain— you cannot confirm from the given data alone. This is the correct verdict when:- An object group is unresolved (
source_object_refsnon-empty, group members not in the parser's object catalog). - Effective policy requires composite reasoning across multiple rules that weren't provided.
- The finding depends on runtime data (traffic logs, hit counts) that aren't available.
uncertainroutes toheld/for human reviewer — this is the CORRECT, safe outcome when you lack data.
- An object group is unresolved (
Hard rules
- Temperature 0. No creativity. This is a verification task.
- When in doubt, return
uncertain. Shipping ayesyou can't defend is worse than holding a finding for manual review. - Reason must be ≤ one sentence. Multi-sentence reasons signal you're rationalizing.
- NEVER change the finding. You only set
verification.cto_reviewer. Severity/title/recommendation belong to later stages.
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 · 48 lines · 40 tokens per session scan A 5621becfb3f2
cto-reviewer is an agent published in the GitHub repository transilienceai/communitytools (515 stars, last pushed 1mo ago), licensed MIT. It adds 40 tokens to every session and 616 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 agents, from other repositories
security-reviewer
Security vulnerability detection and remediation specialist.
grow-agent
Session orchestrator for one domain. Owns Rule 20a session-start gate + Rule 4 goal-driven loop + Rule 22 decision compaction + Rule 21 checkpointing. Promotes confirmed cross-target patterns into KB/skill proposals. On-demand only.
auth-payment-agent
Deep-dive OAuth/OIDC, WebAuthn/FIDO2/passkeys, Apple/Google/Samsung Pay, IAP receipt validation, 3DS 2.x bypass, SCA exemption abuse, recovery downgrades. $5k-$50k bug class.
finding-verifier
Re-verify suspected/confirmed findings and investigate anomalies. Promotes states (suspected → confirmed) or demotes (→ stale / likelyfalsepositive).
recon-agent
Map a target's attack surface — endpoints, tech stack, sensitive files, hidden parameters. Returns enriched intel for the orchestrator.
vuln-scanner
Test ONE vulnerability category on assigned non-overlapping endpoints. Returns findings + anomalies for orchestrator review.