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/yonatangross/orchestkitWrote 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/commands/yonatangross/orchestkit/verify)<a href="https://agentmods.dev/commands/yonatangross/orchestkit/verify"><img src="https://agentmods.dev/badge/commands/yonatangross/orchestkit/verify/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/commands/yonatangross/orchestkit/verify"><img src="https://agentmods.dev/badge/commands/yonatangross/orchestkit/verify.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 | $0.00092 | $0.06852 |
| Opus 5.5 | $0.00037 | $0.02741 |
| Sonnet 5.5 | $0.00018 | $0.01370 |
| Haiku 4.5 | $0.00009 | $0.00685 |
Grade A, and why
verify scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 447 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Auto-generated from skills/verify/SKILL.md
Source: https://github.com/yonatangross/orchestkit
Verify Feature
Host-neutral workflow. Invoke by skill name (verify). Claude Code slash routing, YAML hook loaders, and .claude/chain live in skills/verify/references/claude-code.md.
Comprehensive verification using parallel specialized agents with nuanced grading (0-10 scale) and improvement suggestions.
Quick Start
verify authentication flow
verify --model=opus user profile feature
verify --scope=backend database migrations
Argument Resolution
A pronoun target (this, them, the above) is read back from the conversation, announced in one line, and used: Read("../../shared/rules/target-resolution.md"), inline half.
SCOPE = "$ARGUMENTS" # Full argument string, e.g., "authentication flow"
SCOPE_TOKEN = "$ARGUMENTS[0]" # First token for flag detection (e.g., "--scope=backend")
# $ARGUMENTS[0], $ARGUMENTS[1] etc. for indexed access (CC 2.1.59)
# Model override detection (CC 2.1.72)
MODEL_OVERRIDE = None
for token in "$ARGUMENTS".split():
if token.startswith("--model="):
MODEL_OVERRIDE = token.split("=", 1)[1] # "opus", "sonnet", "haiku", "fable"
SCOPE = SCOPE.replace(token, "").strip()
# Streak gate detection (#2540) — consecutive-pass mode
STREAK_TARGET = None
for token in "$ARGUMENTS".split():
if token.startswith("--streak="):
STREAK_TARGET = int(token.split("=", 1)[1]) # N consecutive READY verdicts required (N >= 2)
SCOPE = SCOPE.replace(token, "").strip()
# When set, apply the Streak Gate (see below). Full protocol: skills/verify/references/streak-gate.md
Pass MODEL_OVERRIDE to all Agent() calls via model=MODEL_OVERRIDE when set. Accepts symbolic names (opus, sonnet, haiku, fable on harnesses whose Agent tool lists it; note fable is premium API spend after 2026-07-12) or full IDs (claude-opus-5-5) per CC 2.1.74.
Opus 5.5: Agents use native adaptive thinking (no MCP sequential-thinking needed). Opus 5.5's own effort default is
medium, one level below Opus 5'shigh, and CC 2.1.280+ starts a newly released model at its default, so passhighorxhighfor verification. Extended 128K output supports comprehensive verification reports.
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.
- 5d ago Changed · +2 lines 9d7b1dc6d29f
- 9d ago Changed · +2 lines 1d9c4d16f8fe
- 17d ago Changed 24fa2def6576
- 21d ago Changed · -40 lines f37eca5d0dda
- 23d ago Changed · +2 lines 95d9173bcbdf
- 24d ago Changed 5fa2781a5aa2
- 1mo ago Changed · -3 lines 3e851995bc81
- 1mo ago Changed 50c770d56003
- 1mo ago Changed · +9 lines e50e09793b98
- 1mo ago First seen · 475 lines · 92 tokens per session scan A b70ce4f941f1
verify is a command published in the GitHub repository yonatangross/orchestkit (295 stars, last pushed yesterday), licensed MIT. It adds 92 tokens to every session and 6,852 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 2026-08-30.
Other commands, from other repositories
verify
You are invoking the verify skill - comprehensive verification following Boris Cherny's pattern.
mockless-tests-block
When this command is used, use the following block. Acknowledge your understanding and then await the user's request.
generate-tests
Comprehensive test suite generation with unit, integration, and end-to-end tests. Analyzes existing code patterns and generates thorough test coverage following testing best practices and project conventions.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.