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/minishlab/semble/antigravitygit clone --depth 1 https://github.com/MinishLab/sembleWhat 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 | $0.00046 | $0.00480 |
| Opus 5 | $0.00023 | $0.00240 |
| Sonnet 5 | $0.00009 | $0.00096 |
| Haiku 4.5 | $0.00005 | $0.00048 |
Grade A, and why
semble-search 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- semble-search — 100% identical, 0 lines differ
- semble-search — 86% identical, 7 lines differ
- semble-search — 86% identical, 6 lines differ
- semble-search — 86% identical, 6 lines differ
- semble-search — 84% identical, 5 lines differ
- semble-search — 84% identical, 5 lines differ
- semble-search — 84% identical, 9 lines differ
- semble-search — 81% identical, 6 lines differ
What it actually says
Use semble search to find code by describing what it does or naming a symbol/identifier, instead of grep:
semble search "authentication flow" ./my-project --max-snippet-lines 10 # first 10 lines only, concise
semble search "save_pretrained" ./my-project # full chunk content
semble search "save model to disk" ./my-project --top-k 10 # more results
Results are cached automatically on first run and invalidated when files change.
Use --content docs to search documentation and prose, --content config for config files (yaml, toml, etc.), or --content all to search code, docs, and config:
semble search "deployment guide" ./my-project --content docs
semble search "database host port" ./my-project --content config
semble search "authentication" ./my-project --content all
Use semble find-related to discover code similar to a known location (pass file_path and line from a prior search result):
semble find-related src/auth.py 42 ./my-project
path defaults to the current directory when omitted; git URLs are accepted.
If semble is not on $PATH, use uvx --from "semble[mcp]" semble in its place.
Workflow
- Start with
semble searchto find relevant chunks. The index is built and cached automatically. - Use
--content docsfor documentation,--content configfor config files, or--content allfor everything. - Navigate directly to the returned file and line. Do not re-search or grep for the same content.
- Optionally use
semble find-relatedwith a promising result'sfile_pathandlineto discover related implementations. - Use grep only when you need every occurrence of a literal string across the whole repo (e.g., all callers of a renamed function).
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 · 44 lines · 46 tokens per session scan A 8448cd2cfcea
semble-search is an agent published in the GitHub repository MinishLab/semble (5,980 stars, last pushed 7d ago), licensed MIT. It adds 46 tokens to every session and 480 once invoked, about $0.0002 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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