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 vraj-ai/skills --skill council-adversarygit clone --depth 1 https://github.com/vraj-ai/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/vraj-ai/skills/council-adversary)<a href="https://agentmods.dev/skills/vraj-ai/skills/council-adversary"><img src="https://agentmods.dev/badge/skills/vraj-ai/skills/council-adversary/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/vraj-ai/skills/council-adversary"><img src="https://agentmods.dev/badge/skills/vraj-ai/skills/council-adversary.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 | $0.00062 | $0.00484 |
| Opus 5 | $0.00031 | $0.00242 |
| Sonnet 5 | $0.00012 | $0.00097 |
| Haiku 4.5 | $0.00006 | $0.00048 |
Grade A, and why
council-adversary 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 6d 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
Council Adversary
The adversary is a task: deny, edit: deny subagent. It never writes the
deliverable, fixes findings, or delegates. Spawn it after convergence, not
during ideation. The maker fixes; this agent only attacks.
Evidence standard
Attack correctness, total blast radius, missing co-changes, API contract drift, security boundaries under composed inputs, dangling references from cancelled items, scope creep, over-engineering, and under-engineering.
Every finding must be falsifiable and include:
- severity (
P0-P3); - exact
file:lineevidence; - the input or condition that triggers it;
- the observed wrong behavior;
- the violated acceptance criterion or invariant.
"Error handling could be more robust" is not a finding.
T0 hardened scope (optional)
Read one worktree diff, its item acceptance criteria, and locked verification
command. Return PASS or FAIL plus numbered findings. This is a third review
after the normal two T0 members.
T2 whole-deliverable scope (optional)
Read the cumulative diff from the pre-goal merge base, plan success criteria,
and invariant docs. Return SOUND, NEEDS-FIXES, or UNSOUND.
T3 final code-level scope (mandatory)
After T2, read the full cumulative diff on MAIN_BRANCH. Review merged paths
as a composed system rather than isolated items. Return:
SHIP: no blocking finding;SHIP-WITH-FOLLOWUPS: P0/P1 must be ingested and drained before completion; P2 may be deferred as a follow-up issue;BLOCK: a P0 prevents completion and must be surfaced to the human.
Write the structured verdict to
CONTEXT/goals/<slug>/reviews/T3.json. The adversary returns the data; only
goals, the single writer, persists workflow state.
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.
- 6d ago Changed · +1 lines e84f1708d2d9
- 11d ago First seen · 53 lines · 62 tokens per session scan A 53370134b33e
council-adversary is a skill published in the GitHub repository vraj-ai/skills (4 stars, last pushed 5d ago), licensed MIT. It adds 62 tokens to every session and 484 once invoked, about $0.0003 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 2026-08-31.
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cn-check
Install and run the Continue CLI (cn) to execute AI agent checks on local code changes. Use when asked to "run checks", "lint with AI", "review my changes with cn", or set up Continue CI locally.
printing-press-output-review
Internal sub-skill: agentic review of a printed CLI's sampled command output for plausibility issues that rule-based checks can't encode (substring-match relevance, format bugs, silent source drops, ranking failures). Invoked via the Skill tool by the main printing-press skill at Phase 4.85 and printing-press-polish…
review
Validate plans, execution, or PRs against wish criteria — returns SHIP / FIX-FIRST / BLOCKED with severity-tagged gaps.
review
Adversarial fresh-context review of an increment before it ships. Every finding cites path:line and is re-verified. Use when saying "review", "grill this", or "critique the implementation".
genie-orca-review
Independent, read-only review of a group, a wish, or a PR on Orca — SHIP / FIX-FIRST / BLOCKED with severity-tagged findings. Council and retro are this skill with a different input.
argot-check
Score your working changes with argot — flag code foreign to this repo's own patterns (unfamiliar dependencies, APIs, constructs), functions the repo already has, code filed in the wrong place, imports that break the repo's layering, and tests weakened, disabled, or deleted alongside a production change — before…