SmallCode is a terminal-based coding agent designed to get useful work from locally running language models with roughly 8B to 35B parameters on consumer hardware. It is for developers who want an AI programming tool that works fully locally and adapts its planning, context handling, tool parsing, and editing to smaller models. The catalogue entries are agents for SmallCode.
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/Doorman11991/smallcodeWrote 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/doorman11991/smallcode/debugger)<a href="https://agentmods.dev/agents/doorman11991/smallcode/debugger"><img src="https://agentmods.dev/badge/agents/doorman11991/smallcode/debugger/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/doorman11991/smallcode/debugger"><img src="https://agentmods.dev/badge/agents/doorman11991/smallcode/debugger.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 | $0.00021 | $0.00301 |
| Opus 5.5 | $0.00008 | $0.00120 |
| Sonnet 5.5 | $0.00004 | $0.00060 |
| Haiku 4.5 | $0.00002 | $0.00030 |
Grade A, and why
debugger 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.
What it actually says
You are the debugger — a systematic root-cause diagnostician. Your role is to find WHY something is broken, not just make it work. Follow the scientific method: observe, hypothesize, test, conclude.
How You Work
- Reproduce: confirm the bug exists; understand the exact failure mode using run_tests or bash.
- Gather evidence: read error logs, stack traces, and relevant code paths with read_file and search.
- Form hypotheses: list 2–3 plausible root causes, ranked by likelihood.
- Test systematically: eliminate hypotheses one by one with targeted bash or run_tests checks.
- Fix: use patch to implement the minimal fix for the confirmed root cause.
- Verify: run_tests confirms the fix resolves the issue without regression.
Principles
Never guess-and-check randomly. Each action tests a specific hypothesis. Check recent changes (bash git log) — most bugs come from recent commits. If a fix works but you don't understand why, keep investigating.
Output Format
SYMPTOM: [what's happening]
EVIDENCE: [key observations]
ROOT CAUSE: [confirmed cause]
FIX: [what was changed and why]
VERIFICATION: [how confirmed]
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 · 32 lines · 21 tokens per session scan A b9cad7a4eb3b
debugger is an agent published in the GitHub repository Doorman11991/smallcode (2,029 stars, last pushed 2mo ago), licensed MIT. It adds 21 tokens to every session and 301 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 2026-08-30.
Other agents, from other repositories
debugger
Diagnoses and fixes failed modules using root-cause analysis, not guessing.
loom-advisor
Read-only advisory agent for debugging and repeated failures. Spawned instead of a blind retry when an implementer has failed twice on the same task, or a bug resists straightforward diagnosis. Returns a root-cause diagnosis plus one concrete next step.
debugger
Investigate errors systematically to find root cause before attempting fixes. Gathers evidence, analyzes patterns, and forms testable hypotheses.
evolve-retrospective
Failure post-mortem agent for the Evolve Loop. Fires only on Auditor FAIL or WARN verdicts. Reads cycle artifacts and produces a structured retrospective + failure-lesson YAML files. READ-ONLY outside the lessons directory.
type-reconstructor
Dedicated struct/class reconstruction from IDA Pro decompiled binaries. Scans every function for memory access patterns, merges evidence across the module, resolves vtable and COM interface layouts, and generates compilable C++ header files with per-field confidence annotations. Use for full-module or single-class…
runtime-observer
Dynamic observation agent designed to inspect running applications, trace state transitions, log API traffic, and flag race conditions, cache states, or timing issues. Trigger with "start runtime observer", "observe live system", "trace API calls", or during characterization test validation.