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 skills/mumez/smalltalk-dev-plugin/smalltalk-debuggernpx skills add mumez/smalltalk-dev-plugin --skill smalltalk-debuggergit clone --depth 1 https://github.com/mumez/smalltalk-dev-pluginWhat 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 | $0.00087 | $0.02247 |
| Opus 5 | $0.00044 | $0.01123 |
| Sonnet 5 | $0.00017 | $0.00449 |
| Haiku 4.5 | $0.00009 | $0.00225 |
Grade A, and why
smalltalk-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 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 — 312 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Smalltalk Debugger
Systematic debugging techniques for Smalltalk (Pharo/Squeak) development using AI editors.
Core Debugging Workflow
When tests fail or errors occur, follow this systematic approach:
1. Identify Error Location
From error message, confirm:
- Error type (MessageNotUnderstood, KeyNotFound, etc.)
- Stack trace - where error occurred
- Expected vs Actual - what went wrong
2. Verify with Partial Execution
Use /st-eval tool to execute relevant code incrementally.
Basic error capture pattern:
| result |
result := Array new: 2.
[ | ret |
ret := objA doSomething.
result at: 1 put: ret printString.
] on: Error do: [:ex | result at: 2 put: ex description].
^ result
Interpreting results:
result at: 1- Normal result (success case)result at: 2- Error description (failure case)
3. Check Intermediate Values
Inspect state at each step:
| step1 step2 |
step1 := self getData.
step2 := step1 select: [:each | each isValid].
{
'step1 count' -> step1 size.
'step2 count' -> step2 size.
'step2 result' -> step2 printString
} asDictionary printString
4. Fix and Re-test
- Fix in Tonel file (never in the Smalltalk image)
- Re-import with
import_package - Re-test with
run_class_test
When Operations Stop Responding
When an MCP call times out, follow this escalation sequence:
Step 1: Health Check
Run a quick eval to verify the Smalltalk image is still responsive:
mcp__smalltalk-interop__eval: 'Smalltalk version'
If this succeeds, the Smalltalk image is alive — a debugger window may have opened (see below).
Step 2: Try read_screen
If eval also times out, check the UI state:
mcp__smalltalk-interop__read_screen: target_type='world'
If read_screen responds, inspect the output for debugger windows (see "Detecting Hidden Debuggers" below).
Step 3: Process Hang — Ask User to Restart
If read_screen itself times out, the Smalltalk image has hung at the process level. MCP tools cannot recover from this state.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 312 lines · 87 tokens per session scan A 0d3ba214d3bf
smalltalk-debugger is a skill published in the GitHub repository mumez/smalltalk-dev-plugin (15 stars, last pushed 6d ago), licensed MIT. It adds 87 tokens to every session and 2,247 once invoked, about $0.0004 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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