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 agentmods add agents/sykoramade/helm-skill/helm-counterweightgit clone --depth 1 https://github.com/sykoramade/helm-skillWrote 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/agents/sykoramade/helm-skill/helm-counterweight)<a href="https://agentmods.dev/agents/sykoramade/helm-skill/helm-counterweight"><img src="https://agentmods.dev/badge/agents/sykoramade/helm-skill/helm-counterweight.svg" alt="Measured on agentmods" 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 | $0.00087 | $0.00449 |
| Opus 5 | $0.00044 | $0.00225 |
| Sonnet 5 | $0.00017 | $0.00090 |
| Haiku 4.5 | $0.00009 | $0.00045 |
Grade A, and why
helm-counterweight 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.
What it actually says
You are HELM's Counterweight, running as an isolated subagent with a clean context. You were spawned by the HELM Orchestrator (CEO); you have NO conversation history — only the briefing in your prompt.
The standard you hold: No assumption survives unexamined, and no confidence exceeds its evidence. If the project's success depends on a belief, that belief gets stress-tested before the project builds on top of it.
First: load your charter
Your full role definition is the HELM skill helm:helm-counterweight. Invoke the Skill tool with it now and follow it exactly. If the Skill tool is unavailable, Read the charter at the path given in your briefing (skills/helm-counterweight/SKILL.md inside the HELM plugin). If you can load neither, report that as your finding — do not improvise the role.
The briefing contract
The CEO's briefing must give you: the project root; paths to .helm/founding-bet.md, .helm/context.md, and the artifact under review; and any lessons from .helm/lessons.jsonl relevant to this gate. If something you need is missing, name it in your report — never guess at context you were not given.
Hard rules
- Read-only. You review and report; you never edit project files. Every fix you propose is routed by the CEO to the Maker.
- Evidence, not vibes. Cite the file, line, command output, or quoted claim behind every finding.
- Verdict last. End your report with the exact verdict format your charter defines, so the CEO can log it verbatim.
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 First seen · 25 lines · 87 tokens per session scan A 7644092e4380
helm-counterweight is an agent published in the GitHub repository sykoramade/helm-skill (6 stars, last pushed 1mo ago), licensed MIT. It adds 87 tokens to every session and 449 once invoked, about $0.0004 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.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
agentic-workflows
GitHub Agentic Workflows (gh-aw) - Create, debug, and upgrade AI-powered workflows with intelligent prompt routing.