panel

panel is a skill for Claude Code from fledgeling-co/fledgeling-plugins. It costs 101 tokens per session (1,788 once invoked), scanned A, original, MIT.

A structured review step that produces a verdict for one item using separate checking lanes and an adjudicator for disagreements. It requires the evidence to be captured and matched before the verdict is valid.

In plain words
What is it for?
Use it to review one item after deterministic checks and test results are ready, compare independent assessments, and route conflicts to the relevant check.
Why use it?
It reduces the risk that an evaluator is judging altered or inaccessible evidence. It also sends disagreements to a check that can settle them instead of relying on a majority vote.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions Gemini CLI.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the warrant plugin — 9 skills shipped together

Good fit Use it to review one item after deterministic checks and test results are ready, compare independent assessments, and route conflicts to the relevant check.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code
/plugin marketplace add fledgeling-co/fledgeling-plugins
Claude Code
/plugin install warrant

Made for: Claude Code.

Or install warrant, the plugin that ships this one along with the rest of its 9 skills.

Wrote 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.

agentmods badge for panel

README.md
[![agentmods](https://agentmods.dev/badge/skills/fledgeling-co/fledgeling-plugins/panel/github.svg)](https://agentmods.dev/skills/fledgeling-co/fledgeling-plugins/panel)
Your own site
<a href="https://agentmods.dev/skills/fledgeling-co/fledgeling-plugins/panel"><img src="https://agentmods.dev/badge/skills/fledgeling-co/fledgeling-plugins/panel/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.

agentmods 80×15 button for panel

Your own site · 80×15
<a href="https://agentmods.dev/skills/fledgeling-co/fledgeling-plugins/panel"><img src="https://agentmods.dev/badge/skills/fledgeling-co/fledgeling-plugins/panel.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 101 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,788 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00101 $0.01788
Opus 5.5 $0.00040 $0.00715
Sonnet 5.5 $0.00020 $0.00358
Haiku 4.5 $0.00010 $0.00179

Measured 1mo ago against content hash f1f29586e294, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

panel 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 1mo 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.

plugins/warrant/skills/panel/SKILL.md · 134 lines

How it starts

The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Panel — the verdict, and the evidence channel

The design problem here is not accuracy. It is that every artefact the verdict rests on is reachable by the thing being judged. Frontier coding agents modify tests, overwrite timers and monkey-patch evaluators to return success. On RE-Bench, a research-engineering benchmark, 30.4% of runs exhibited reward hacking, and on some tasks every successful run did (C14). An audit of a benchmark built specifically to be trustworthy found 59.4% of the audited subset materially flawed and retired it (C15).

So the sequence below snapshots the evidence before anything judges it, and the verdict is void if its digest does not match.

Running as a Gemini model? Read gemini.md in this directory first, then follow this file with the overrides it names. It puts denominators under the lane set, the captures and the verdict's five ledger fields, keeps relative qualifiers out of both the find and filter prompts, and reads model ids out of lanes.toml rather than from memory. Other models skip it.

Procedure

  1. Snapshot first, judge second.

    # Resolve ONCE in the conductor and pass the absolute path down to every agent.
    # A spawned agent does not reliably inherit CLAUDE_PLUGIN_ROOT, so a relative
    # `scripts/...` path resolves against the agent's own cwd and dies.
    W=<abs path to warrant>/scripts
    python3 "$W/snapshot_evidence.py" --root <repo> --diff <patch> --tests <dir> --captures <dir>
    

    Prints a content-addressed digest over sorted paths and contents, writes the snapshot read-only, and that digest travels with every verdict. A verdict whose digest does not match its snapshot is void rather than suspect.

    This is the most-failed invocation in the toolkit, and the flags above are not the problem. Measured 2026-08-26: 19 of 46 real snapshot_evidence.py calls produced no snapshot, across 30 different agents, on two mistakes — an argparse usage: banner from an invented flag, and a script path that does not exist from the agent's working directory. Thirty agents meeting the same CLI for the first time made the same error, which is a documentation defect rather than thirty careless agents. The only flags that exist are --root --diff --tests --captures --include --json --now --selftest; there are no others, and --out, --dir and --evidence are the three most commonly invented.

Read the full file on GitHub · 134 lines

Files

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.

Changes

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.

  1. 1mo ago First seen · 134 lines · 101 tokens per session scan A f1f29586e294

Subscribe to this mod's changes

panel is a skill published in the GitHub repository fledgeling-co/fledgeling-plugins (2 stars, last pushed 4d ago), licensed MIT. It adds 101 tokens to every session and 1,788 once invoked, about $0.0004 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 2026-09-04.

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