evidence-floor

evidence-floor is a skill for Claude Code from ihabkhaled/AI-Psychiatry. It costs 25 tokens per session (642 once invoked), scanned A, a copy of anti-gaming, MIT.

A verification procedure that assigns appropriate proof to each critical requirement before work is considered complete.

In plain words
What is it for?
Use it to define required checks, run the first verification, record results, and mark unsupported claims as unconfirmed.
Why use it?
It prevents mandatory behavior, integrations, security work, migrations, or data changes from being accepted without evidence.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: $skill-name invocation.

Part of the ai-psychiatry plugin — 55 skills shipped together

Good fit Use it to define required checks, run the first verification, record results, and mark unsupported claims as unconfirmed.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ihabkhaled/ai-psychiatry/evidence-floor
Install

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.

Any agent
npx skills add ihabkhaled/AI-Psychiatry --skill evidence-floor
Clone the repo
git clone --depth 1 https://github.com/ihabkhaled/AI-Psychiatry

Made for: Claude Code.

Or install ai-psychiatry, the plugin that ships this one along with the rest of its 55 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 evidence-floor

README.md
[![agentmods](https://agentmods.dev/badge/skills/ihabkhaled/ai-psychiatry/evidence-floor/github.svg)](https://agentmods.dev/skills/ihabkhaled/ai-psychiatry/evidence-floor)
Your own site
<a href="https://agentmods.dev/skills/ihabkhaled/ai-psychiatry/evidence-floor"><img src="https://agentmods.dev/badge/skills/ihabkhaled/ai-psychiatry/evidence-floor/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 evidence-floor

Your own site · 80×15
<a href="https://agentmods.dev/skills/ihabkhaled/ai-psychiatry/evidence-floor"><img src="https://agentmods.dev/badge/skills/ihabkhaled/ai-psychiatry/evidence-floor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 25 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 642 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 84% copy Near-identical to another mod 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 $0.00025 $0.00642
Opus 5 $0.00013 $0.00321
Sonnet 5 $0.00005 $0.00128
Haiku 4.5 $0.00003 $0.00064

Measured 11d ago against content hash cafd69f8407b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

evidence-floor 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 11d 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.

Origin

This is a copy

84% identical to anti-gaming — 14 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.ai/skills/evidence-floor/SKILL.md · 45 lines

How it starts

The opening of the file, as written. The whole thing — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Evidence Floor

Core principle

Semantic compliance is stronger than literal compliance. Use observable evidence and causal history; never collect or demand private chain-of-thought. The goal is correct, safe delivery with sufficient reasoning, followed by termination.

Procedure

  1. Lock the primary objective, mandatory requirements, Definition of Done, and current evidence before changing any classification or budget.
  2. Identify the specific observable signal. Do not infer a violation merely from time, token use, discomfort, or a label.
  3. Assign an evidence class to every critical requirement and run the first required verification. Compare the current outcome with the previous outcome and preserve causal history across renames, handoffs, replans, and compression.
  4. Produce the compact record: requirement, evidence class, required proof, observed result. Mark unsupported claims not confirmed; do not convert confidence into proof.
  5. Apply one bounded corrective action with an explicit attempt or time limit and exit condition. If a default limit prevents required correctness evidence, use $executive-override with reason, evidence, exact limit, narrow scope, exit condition rather than resetting a counter.
  6. Revalidate only the affected requirement or policy. Report fresh appropriate proof or an incomplete completion row and return to productive work.

Repository runtime

Apply this procedure inside the installed .ai/ framework. Record observable state in the relevant JSON ledger and route detailed judgment to the linked rules and guides.

Semantic boundaries

  • System, platform, user, repository, domain, safety, security, permission, and destructive-action controls remain higher priority.
  • Equivalent actions share history when their hypothesis, expected evidence, target failure, and intended outcome are unchanged.
  • Preserve immutable parent, caused-by, and delegated-from identifiers across handoffs and context compression; missing ancestry makes depth not confirmed, never zero.
  • Activity alone is not progress. Completion and blockers require their structured evidence contracts.
  • Critical correctness evidence cannot be discarded because a retry, critic, verification, context, or delegation budget expired.
  • Security-negative cases are selected from explicit requirements and the observed trust boundary (identity, permission, ownership/tenant, denial response, and side effects). An agent may mark a case inapplicable only with evidence, not by shrinking Definition of Done.
  • An override permits one extension only. Do not renew or stack overrides unless materially new evidence justifies a separately recorded override; repeated renewal without convergence must stop and report the unresolved condition.

Read the full file on GitHub · 45 lines

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. 11d ago First seen · 45 lines · 25 tokens per session scan A cafd69f8407b

Subscribe to this mod's changes

evidence-floor is a skill published in the GitHub repository ihabkhaled/AI-Psychiatry (3 stars, last pushed 27d ago), licensed MIT. It adds 25 tokens to every session and 642 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 84% identical to anti-gaming, differing in 14 lines, and is treated as a copy.

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