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 gohypergiant/agent-skills --skill accelint-qrspi-applygit clone --depth 1 https://github.com/gohypergiant/agent-skillsWrote 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/gohypergiant/agent-skills/accelint-qrspi-apply)<a href="https://agentmods.dev/skills/gohypergiant/agent-skills/accelint-qrspi-apply"><img src="https://agentmods.dev/badge/skills/gohypergiant/agent-skills/accelint-qrspi-apply/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/gohypergiant/agent-skills/accelint-qrspi-apply"><img src="https://agentmods.dev/badge/skills/gohypergiant/agent-skills/accelint-qrspi-apply.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 7 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 244 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- high Memory Poisoning · line 338 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
- high Memory Poisoning · line 344 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
- high Memory Poisoning · line 655 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
- high Memory Poisoning · line 658 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
- high Memory Poisoning · line 660 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
- medium Excessive Agency · line 718 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00135 | $0.10358 |
| Opus 5 | $0.00068 | $0.05179 |
| Sonnet 5 | $0.00027 | $0.02072 |
| Haiku 4.5 | $0.00014 | $0.01036 |
Grade A, and why
accelint-qrspi-apply 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 today.
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 — 931 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Accelint QRSPI Apply
Implement OpenSpec changes with intelligent parallelization. This skill orchestrates parallel sub-agent execution based on dependency analysis in the OpenSpec task file, validates implementation, and manages the complete apply workflow.
What This Skill Does
Automates: The implementation phase of spec-driven development with parallel execution Scope: Task implementation → Validation → Archive readiness Output: Fully implemented change ready for archival
Does NOT: Create plans, modify specs, or automatically archive (suggests archival when ready)
Prerequisites
- OpenSpec CLI installed and initialized
- OpenSpec change created via
accelint-qrspiskill (includes "Parallelization Strategy" in tasks.md) - Sub-agent support (for parallel execution)
- The expanded OpenSpec workflows (
explore,new,continue) enabled
Important: This skill is specifically designed for QRSPI-planned changes. Standard OpenSpec changes without parallelization strategies should use the regular openspec-apply-change skill directly.
Workflow Overview
┌─────────────────────────────────────────────────────────────────┐
│ Stage Action Output │
├─────────────────────────────────────────────────────────────────┤
│ Preflight Select and validate change Ready to proceed │
│ Start Time Record started_at timestamp Telemetry marker │
│ Parse Extract parallelization Dependency graph │
│ Dependencies Identify blocking tasks Execution plan │
│ Load Context Read config.yaml context Project context │
│ Execute Run slices (parallel/serial) Implemented code │
│ Update Docs Sync living documents Updated docs │
│ Complete Time Record completed_at timestamp Telemetry marker │
│ Verify Run opsx:verify Verification rpt │
└─────────────────────────────────────────────────────────────────┘
Implementation Steps
What ships with it
2 files 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.
- today Changed · +33 lines b1f65f0180b0
- 7d ago Changed dd08cc0ed767
- 8d ago Changed · +69 lines f0a0729e7fac
- 12d ago First seen · 829 lines · 135 tokens per session scan A 52f041bf32e8
accelint-qrspi-apply is a skill published in the GitHub repository gohypergiant/agent-skills (24 stars, last pushed today), licensed Apache-2.0. It adds 135 tokens to every session and 10,358 once invoked, about $0.0007 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 2026-08-30.
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