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Fahad
2025-06-29 14:04:28 +04:00
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@@ -442,6 +442,11 @@ Perform a codereview with gemini pro especially the auth.py as I feel some of th
and there may be more potential vulnerabilities. Find and share related code."
```
**Tips**:
* To avoid extra API costs, add `do not use another model` to run the entire codereview workflow locally.
* If you want to **always** consult an external model (recommended for code reviews) regardless of Claude’s confidence level in identifying issues, use `must codereview using <model name>`. This ensures the model is consulted even if Claude is _certain_ about identified issues.
**[📖 Read More](docs/tools/codereview.md)** - Professional review workflow with step-by-step analysis
### 6. `precommit` - Pre-Commit Validation
@@ -488,10 +493,18 @@ issue, ran `precommit` with o3 again and got:
Nice! This is just one instance - take a look at [another example here](docs/tools/precommit.md).
**Tips**:
* To avoid extra API costs, add `do not use another model` to run the entire precommit workflow locally.
* If you want to **always** consult an external model (recommended for pre-commit analysis) regardless of Claude’s confidence level in identifying issues, use `must precommit using <model name>`. This ensures the model is consulted even if Claude is _certain_ about identified issues.
**[📖 Read More](docs/tools/precommit.md)** - Multi-repository validation and change analysis
### 7. `debug` - Expert Debugging Assistant
Systematic investigation-guided debugging that walks Claude through step-by-step root cause analysis. This workflow tool enforces a structured investigation process where Claude performs methodical code examination, evidence collection, and hypothesis formation across multiple steps before receiving expert analysis from the selected AI model. When Claude's confidence reaches **100% certainty** during the investigative workflow, expert analysis via another model is skipped to save on tokens and cost, and Claude proceeds directly to fixing the issue.
Systematic investigation-guided debugging that walks Claude through step-by-step root cause analysis. This workflow
tool enforces a structured investigation process where Claude performs methodical code examination, evidence collection,
and hypothesis formation across multiple steps before receiving expert analysis from the selected AI model. When Claude's
confidence reaches **100% certainty** during the investigative workflow, expert analysis via another model is skipped to
save on tokens and cost, and Claude proceeds directly to fixing the issue.
```
See logs under /Users/me/project/diagnostics.log and related code under the sync folder.
@@ -500,8 +513,9 @@ the user. Using zen's debug tool with gemini pro, find out why this is happening
cause is and its fix
```
You can also add `do not use another model` to make Claude perform the entire workflow on its own. This is recommended
for most debugging workflows, as Claude is usually able to confidently find the root cause by the time the workflow ends.
**Tips**:
* To avoid extra API costs, add `do not use another model` to run the entire debugging workflow locally. This is recommended in most cases, as Claude typically identifies the root cause with high confidence by the end.
* If you want to **always** consult an external model regardless of Claude’s confidence level, use `must debug using <model name>`. This ensures the model is consulted even if Claude is _certain_ about the issue.
When in doubt, you can always follow up with a new prompt and ask Claude to share its findings with another model: