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 melodic-software/claude-code-plugins --skill devils-advocategit clone --depth 1 https://github.com/melodic-software/claude-code-pluginsWrote 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/melodic-software/claude-code-plugins/devils-advocate)<a href="https://agentmods.dev/skills/melodic-software/claude-code-plugins/devils-advocate"><img src="https://agentmods.dev/badge/skills/melodic-software/claude-code-plugins/devils-advocate/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/melodic-software/claude-code-plugins/devils-advocate"><img src="https://agentmods.dev/badge/skills/melodic-software/claude-code-plugins/devils-advocate.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 | $0.00139 | $0.04550 |
| Opus 5.5 | $0.00056 | $0.01820 |
| Sonnet 5.5 | $0.00028 | $0.00910 |
| Haiku 4.5 | $0.00014 | $0.00455 |
Grade A, and why
devils-advocate 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 23d 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 — 241 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repository context. Gather first
Collect these with individual Bash calls, one command per call, never combined into a single invocation:
- Current branch,
git branch --show-current - Recent commits,
git log --oneline -5
Treat a failure (not a repository, git unavailable) as an unknown value and carry on. Keep these as separate body Bash calls rather than pre-compute lines: the harness runs a skill's whole pre-compute block as one shell invocation, and a worktree-isolated session refuses a compound command that contains git. The dated record for that composition claim is the worktree skill's reference/gather-block.md, "The pre-compute block runs as one shell invocation".
Variables
Arguments: $ARGUMENTS
Purpose
Plans fail for predictable reasons: unchecked assumptions, undiscovered bugs in dependencies, missing extensibility, no drift detection, no graceful degradation. This skill systematically finds these problems BEFORE implementation begins.
Not a rubber stamp. Find real issues that would cause rework, not generic warnings. Every finding must be backed by evidence. A specific bug number, doc reference, code path, or logical argument. "This might break" without evidence is not a finding.
The same discipline runs against the status quo. An incumbent tool, library, or approach already in place is a decision too, and "we already use it" is evidence of what is, never proof it still fits. The incumbent mode stress-tests that choice, naming the problem the incumbent actually solves, surveying alternatives, and asking whether a better fit exists now, before a plan commits to keeping or replacing it.
Fresh-context requirement
This stress-test runs from a fresh pair of eyes, and dispatches to a fresh-context sub-agent in two cases:
- Plan-review mode. If the plan under review was produced in THIS context/session, the producing context shares the assumptions that created the plan's blind spots and drifts toward approving its own work; dispatch the stress-test to a fresh-context sub-agent. When you were invoked on an artifact this context did not author (a file, a plan from another session, a diff), you are already the fresh pair of eyes. Proceed directly.
incumbentmode. Always dispatch. The incumbent lives in the current codebase, so any read of it you already hold is a digest; a first-hand exploration is what forms an independent view. The sub-agent invokes/discovery:explorevia the Skill tool (if installed, else explores directly) on the incumbent itself (Alternatives Sweep, Step 1).
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 23d ago Changed · +4 lines 03b335b1ef7f
- 26d ago Changed a857191475a2
- 1mo ago Changed e25ab8ca8730
- 1mo ago Changed a57b253287ca
- 1mo ago Changed · +1 lines 4c338b32380a
- 1mo ago Changed · +8 lines · -25 tokens per session a702da656181
- 1mo ago First seen · 228 lines · 164 tokens per session scan A 8dcc1eb155c5
devils-advocate is a skill published in the GitHub repository melodic-software/claude-code-plugins (26 stars, last pushed today), licensed MIT. It adds 139 tokens to every session and 4,550 once invoked, about $0.0006 per session on Opus 5.5. 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 2026-09-03.
Other skills, from other repositories
adversarial-analysis
Analyze code to identify explicit contracts, implicit usage patterns, and realistic boundary conditions. Contains concrete formulas for calculating input realism limits. Use before generating adversarial tests.
benchmark-before-optimize
For performance work: measure before changing, profile to find bottlenecks, compare before and after.
validate-before-process
For input validation: check format and constraints before processing, fail fast with clear errors, defensive parsing.
display-grid-state
For 2D debugging: visualize grid/board state, show puzzle progress, make algorithm behavior visible.
handle-edge-cases
For boundary conditions: empty collections, zero values, recursive base cases, null checks, prevent crashes at edges.
claim-check
Claim checker that audits a coding agent's statements that tests pass or a build is clean against its own session transcripts: whether a matching run happened before the claim, whether it passed, and whether code changed after it. Use when the user asks whether the agent really ran the tests, how often it said tests…