praxflow-embedded
Skill1 starsChanged 2 months agoMITView on GitHub
Embedded-systems domain pack for PraxFlow. Use alongside PraxFlow workflows/skills when working on MCU, RTOS, embedded Linux, QNX, device drivers, firmware, hardware protocols, registers, interrupts, DMA, cache, CAN/SPI/UART, or real target devices. Adds embedded evidence authority, review risks, and target-aware verification guidance without replacing project-specific build/deploy/debug skills.
In this repository11 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- develop-featureSkill
- diagnoseSkill
- fix-bugSkill
- grillSkill
- plan-changeSkill
- review-changeSkill
- surveySkill
- traceSkill
- understand-projectSkill
The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 4 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈4
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 15
Read the relevant references as needed:
- Distinctive: line 49
run CAN/bus tests;
- Distinctive: line 58
Use explicit Decision Gates for consequential choices such as:
- Distinctive: line 67
Do not ask engineers factual questions that code, schematics/project docs, or authoritative references can answer.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
PraxFlow Embedded
Apply this pack as an augmentation to the active PraxFlow Workflow or Skill. Do not replace the Core method and do not duplicate project-specific capabilities.
Read the relevant references as needed:
references/evidence.md— evidence authority, applicability, Datasheet/Errata/standard/reference-implementation handling.references/review.md— embedded-specific review dimensions.references/verification.md— build/target/device verification strategy.references/guidance.md— recurring embedded reasoning guardrails.
Core embedded stance
Embedded work frequently combines software inference with external physical facts. Treat the following as high-risk for unsupported guessing:
- registers and bit fields;
- initialization/reset sequences;
- silicon errata;
- interrupt-context behavior;
- DMA and cache coherency;
- memory ownership/alignment/lifetime;
- timing and realtime behavior;
- watchdog/reset behavior;
- protocol fields and wire timing;
- ABI/packing/endian assumptions;
- hardware state that is only observable on a target.
Model memory may suggest what to inspect, but it is not sufficient authority for consequential hardware/protocol facts when applicable references are available.
Interaction with project capabilities
This pack does not define commands such as:
- build;
- flash/download;
- deploy;
- open serial;
- SSH target;
- run CAN/bus tests;
- JTAG debugger commands.
Those belong to the consuming project.
The pack instead tells the active Workflow when and why those capabilities provide stronger evidence.
Human decision boundaries
Use explicit Decision Gates for consequential choices such as:
- changing a deployed protocol or persistent format;
- altering interrupt/thread ownership;
- accepting data loss or retry semantics;
- changing realtime/resource budgets;
- disabling safety/watchdog behavior;
- operations that can brick, damage, or irreversibly reconfigure hardware.
Do not ask engineers factual questions that code, schematics/project docs, or authoritative references can answer.
Completion stance
For behavior that depends on hardware or a real target, static reasoning or a successful host build is usually incomplete evidence. Use proportionate target/device verification when the capability exists and the claim depends on real hardware behavior.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

