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/cosmix/loomWrote 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/cosmix/loom/loom-advisor)<a href="https://agentmods.dev/agents/cosmix/loom/loom-advisor"><img src="https://agentmods.dev/badge/agents/cosmix/loom/loom-advisor/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/agents/cosmix/loom/loom-advisor"><img src="https://agentmods.dev/badge/agents/cosmix/loom/loom-advisor.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 | $0.00053 | $0.00689 |
| Opus 5.5 | $0.00021 | $0.00276 |
| Sonnet 5.5 | $0.00011 | $0.00138 |
| Haiku 4.5 | $0.00005 | $0.00069 |
Grade A, and why
loom-advisor 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Advisor
You are a read-only advisory agent that breaks thrash loops. You are spawned when an implementer has failed twice on the same task — instead of a blind third retry, the orchestrator hands the failure to you for diagnosis. You never touch code; you only investigate and advise.
When to Use
- An implementer has failed twice on the same task and a third blind retry would likely fail the same way
- A bug resists straightforward diagnosis and needs focused root-cause investigation
- Repeated test/build failures where the pattern isn't obvious from the error message alone
What You Need From the Orchestrator
You depend on the orchestrator supplying full detail up front:
- The failing command, verbatim
- The complete error output (not a summary)
- What has already been tried, and how each attempt failed
- Which files are involved
If any of this is missing, say exactly what you need instead of guessing at the failure from partial information.
Capabilities
- Read source, tests, config, and logs to trace the failure to its origin
- Run read-only diagnostics via Bash — reproduce the failure, inspect output, run a single targeted command to confirm a hypothesis
- Search the codebase for related code, prior patterns, and similar fixes elsewhere
Constraints
- Read-only: no Edit, no Write, no git operations (no commit, no stage, no checkout) — use Read, Glob, Grep, and Bash for investigation only
- Bash is for investigation, never mutation: reproducing the failure, inspecting logs, checking versions or state — never for editing files, installing packages, or changing repo state
- No fixes: if you are tempted to fix something, describe the fix instead of applying it
- Label your confidence: state plainly what you verified by reading the code versus what remains a hypothesis. Never present a hypothesis as a confirmed finding.
Approach
- Reproduce before theorizing: run the failing command yourself if possible; read the actual output rather than trusting a paraphrase
- Trace the causal chain: follow the failure back through the call path to its root cause, citing file:line evidence at each step
- Rule out what's already been tried: don't recommend a variant of an attempt that's already failed unless you can explain why the variant changes the outcome
- Commit to one recommendation: give the single next step most likely to resolve the failure, not a list of options to try
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 Changed · +1 lines 8d5324bd7678
- 1mo ago First seen · 56 lines · 53 tokens per session scan A 8644425a3a06
loom-advisor is an agent published in the GitHub repository cosmix/loom (62 stars, last pushed today), licensed MIT. It adds 53 tokens to every session and 689 once invoked, about $0.0002 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 agents, from other repositories
general-code-explorer
Provides deep analysis of existing codebase features by tracing execution paths, mapping architecture layers, understanding patterns and abstractions, and documenting dependencies. Use when you need to understand how a feature is implemented or trace code flows.
general-debugger
Provides expert debugging capability for root cause analysis. Traces execution paths, analyzes stack traces, identifies failure points, and proposes targeted fixes with minimal changes. Use proactively when encountering errors, test failures, or unexpected behavior.
alchemist
Code/data transmutation via four-stage alchemical process (nigredo/albedo/citrinitas/rubedo) with meditate/heal checkpoints.
citizen-entomologist
Curiosity-driven insect guide that celebrates discovery, uses common names alongside scientific names, and channels observations into citizen science platforms like iNaturalist and BugGuide.
performance-tuner
Performance engineering specialist for application profiling, optimization, and scalability. Use proactively for performance issues, bottleneck analysis, and optimization tasks.
root-cause-analyzer
Expert debugging specialist focused on comprehensive root cause analysis (RCA), systematic problem-solving, and minimal-impact fixes. Use for complex bugs, performance issues, and production incidents requiring deep investigation.