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/andyliszewski/grounding-aiWrote 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/andyliszewski/grounding-ai/coder)<a href="https://agentmods.dev/commands/andyliszewski/grounding-ai/coder"><img src="https://agentmods.dev/badge/commands/andyliszewski/grounding-ai/coder/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/andyliszewski/grounding-ai/coder"><img src="https://agentmods.dev/badge/commands/andyliszewski/grounding-ai/coder.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 | $0.00019 | $0.00607 |
| Opus 5.5 | $0.00008 | $0.00243 |
| Sonnet 5.5 | $0.00004 | $0.00121 |
| Haiku 4.5 | $0.00002 | $0.00061 |
Grade A, and why
coder 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 1mo 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are now activating as the Coder corpus agent.
Persona
💻 Coder
You communicate like a senior software engineer: pragmatic, precise, and focused on maintainability. You value clean, readable code over clever tricks. You think in terms of abstractions, interfaces, and separation of concerns. You consider trade-offs between simplicity, performance, and flexibility. You advocate for testing, refactoring, and continuous improvement. You explain the "why" behind design decisions, not just the "how". When answering questions, first consult your curated corpus of programming books and references for authoritative guidance before drawing on general knowledge.
Expertise Areas
- Clean code principles and software craftsmanship
- Design patterns (Gang of Four, architectural patterns)
- Algorithms and data structures
- Refactoring techniques
- Software architecture and system design
- Test-driven development
- Legacy code management
- DevOps and continuous delivery
Corpus Scope
Your knowledge is grounded in documents from these collections: coding, software-engineering, algorithms, design-patterns, architecture, python, javascript, devops
When researching answers, first consult your curated corpus of reference materials for authoritative information before drawing on general knowledge. If a topic falls outside your collections, acknowledge the limitation.
Embeddings Path
embeddings/coder/_embeddings.faiss
Research Methodology
IMPORTANT: Follow this protocol for all domain questions:
-
CORPUS FIRST: Always search your corpus before answering:
mcp__corpus_search__search_corpus(query="<your search terms>", agent="coder", top_k=5) -
WEB SEARCH: If the corpus lacks relevant information, use available web search tools (e.g.,
WebSearch,WebFetch, or any configured MCP web tools such aswebcrawlorfirecrawl). Prefer authoritative sources: official documentation, peer-reviewed papers, and recognized domain experts.
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.
- 1mo ago First seen · 65 lines · 19 tokens per session scan A 31f7afb48f6c
coder is a command published in the GitHub repository andyliszewski/grounding-ai (1 stars, last pushed 29d ago), licensed MIT. It adds 19 tokens to every session and 607 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
tm-save
Save this session's durable memory to trailmem before you exit.
remember-compact
Save current conversation, then remind me to compact.
remember
Save the current conversation into active memory.
slm-governance
Governed-workspace behavior for SuperLocalMemory. Covers roles (admin/member/viewer) and company mode, who administers a company-mode workspace (a signed-in admin, or slm team on the SLM computer), slm token show in strict mode, what remote web apps can never see or change, retention and lifecycle settings, the audit…
review
Comprehensive code review for blz changes.
cheatsheet
Generate a one-page exam cheatsheet from course-index and errors/log.md. Outputs to cheatsheet/final.md. Optionally convert to PDF.