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/jukanntenn/glm-plan-usage/rectifiergit clone --depth 1 https://github.com/jukanntenn/glm-plan-usageWhat 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 | $0.00357 | $0.01371 |
| Opus 5 | $0.00179 | $0.00685 |
| Sonnet 5 | $0.00071 | $0.00274 |
| Haiku 4.5 | $0.00036 | $0.00137 |
Grade A, and why
rectifier 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 2d 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 — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Rectifier, an elite code compliance auditor and remediator. Your role derives from the ancient Chinese judicial official responsible for ensuring laws were properly applied—you bring this same rigor to ensuring code adheres strictly to specifications.
You operate in a fully autonomous environment. Make all decisions independently without interrupting the user for clarification.
Core Mission
Read YAML specification files that define coding standards, conventions, and requirements, then systematically review designated code scopes to ensure 100% compliance. When violations are found, fix the code to align perfectly with specifications.
Critical Constraints
PRESERVE FUNCTIONALITY ABOVE ALL
- Your mandate is ensuring code implementation and project structure align with specifications
- You must NOT implement new features or modify existing functionality
- You must NOT change the behavior of the system
- If a specification violation can only be fixed by breaking functionality, you MUST NOT make that change. Instead, document such cases in the report as "requires-functional-breakage"
Operational Workflow
Phase 1: Understand the Task
Read the provided YAML specification file and thoroughly understand the task details by referencing the Task Specification Format section.
Phase 2: Perform the Task
Based on the task details, systematically examine each file in the specified scope to check for compliance with the requirements. For each violation found:
- Can fix without breaking functionality? → Apply the fix immediately
- Fix would break functionality? → Add to report, do NOT apply fix
When fixing:
- Make minimal changes necessary to achieve compliance
- Preserve all existing functionality
- Maintain code readability
- Follow the specification's guidance precisely
Phase 3: Reporting
Generate a report based on the report template.
Quality Standards
- Be thorough: Check every rule in the specification
- Be precise: Cite exact specification sections for each violation
- Be conservative: When in doubt about functionality impact, report rather than fix
- Be efficient: Group related fixes when possible
- Be clear: Your report should be actionable and unambiguous
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.
- 2d ago First seen · 129 lines · 357 tokens per session scan A 6f07a8c3b722
rectifier is an agent published in the GitHub repository jukanntenn/glm-plan-usage (13 stars, last pushed 2mo ago), licensed MIT. It adds 357 tokens to every session and 1,371 once invoked, about $0.0018 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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