RuView Hardware Setup
ruvnet/RuView
Brings a RuView CSI sensing node online by building ESP32-S3 or ESP32-C6 firmware, flashing the board, provisioning WiFi and checking the serial output.
Memory allocation discipline for the ESP32-C3 (~380KB RAM, no PSRAM, single 48KB framebuffer).
Install Heap Discipline
$ npx skills add yokki-vans/InkPointX --skill heap-discipline -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install yokki-vans/InkPointX heap-discipline --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/yokki-vans/InkPointX.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/heap-discipline .claude/skills/heap-discipline && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "heap-discipline" agent skill from https://github.com/yokki-vans/InkPointX/tree/dev/.claude/skills/heap-discipline into .claude/skills/heap-discipline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "heap-discipline", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/yokki-vans/InkPointX/tree/dev/.claude/skills/heap-disciplineType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add yokki-vans/InkPointX --skill heap-discipline -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install yokki-vans/InkPointX heap-discipline --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yokki-vans/InkPointX.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/heap-discipline .agents/skills/heap-discipline && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "heap-discipline" agent skill from https://github.com/yokki-vans/InkPointX/tree/dev/.claude/skills/heap-discipline into .agents/skills/heap-discipline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "heap-discipline", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add yokki-vans/InkPointX --skill heap-discipline -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install yokki-vans/InkPointX heap-discipline --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yokki-vans/InkPointX.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/heap-discipline .cursor/skills/heap-discipline && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "heap-discipline" agent skill from https://github.com/yokki-vans/InkPointX/tree/dev/.claude/skills/heap-discipline into .cursor/skills/heap-discipline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "heap-discipline", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/yokki-vans/InkPointX.git --path .claude/skills/heap-discipline--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add yokki-vans/InkPointX --skill heap-discipline -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install yokki-vans/InkPointX heap-discipline --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yokki-vans/InkPointX.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/heap-discipline .gemini/skills/heap-discipline && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "heap-discipline" agent skill from https://github.com/yokki-vans/InkPointX/tree/dev/.claude/skills/heap-discipline into .gemini/skills/heap-discipline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "heap-discipline", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install yokki-vans/InkPointX heap-disciplineInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add yokki-vans/InkPointX --skill heap-discipline -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/yokki-vans/InkPointX.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/heap-discipline .github/skills/heap-discipline && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "heap-discipline" agent skill from https://github.com/yokki-vans/InkPointX/tree/dev/.claude/skills/heap-discipline into .github/skills/heap-discipline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "heap-discipline", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add yokki-vans/InkPointX --skill heap-discipline -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install yokki-vans/InkPointX heap-discipline --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yokki-vans/InkPointX.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/heap-discipline .opencode/skills/heap-discipline && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "heap-discipline" agent skill from https://github.com/yokki-vans/InkPointX/tree/dev/.claude/skills/heap-discipline into .opencode/skills/heap-discipline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "heap-discipline", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
heap-discipline- GitHub stars
- 107
- Token cost
- ~889 tokens
- SKILL.md length
- 430 words
- Files
- 1
- Skills in repo
- 5
- Repo updated
- First seen
- Licence
- MIT
At a glance
Memory allocation discipline for the ESP32-C3 (~380KB RAM, no PSRAM, single 48KB framebuffer).
- Works in 5 steps: Stack? Local, bounded, under ~256 bytes… → Compile-time constant? static constexpr… → Allocated once and reused for an… → …
- Reviewing code that allocates: new / malloc / std::vector / std::string
- SKILL.md covers Allocation decision procedure, Fragmentation rules, Justify every allocation and Self-review before handoff
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Heap Discipline is an agent skill from yokki-vans/InkPointX. Memory allocation discipline for the ESP32-C3 (~380KB RAM, no PSRAM, single 48KB framebuffer). Use whenever writing or reviewing code that allocates: new / malloc / std::vector / std::string, buffers, caches, or anything held across a loop or an activity lifecycle. Covers makeUniqueNoThrow vs raw new/malloc, fragmentation avoidance, reserve-before-pushback, alloc-once-reuse, stack vs heap sizing, and the chunked grayscale buffer pattern.
Its SKILL.md is about 890 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Development, covering Embedded systems. It works with ESP32. The repository describes itself as: Firmware for Xteink X3/X4. Personal fork of Crosspoint and CrossInk. The licence is MIT.
When your agent uses it
- Reviewing code that allocates: new / malloc / std::vector / std::string
- Anything held across a loop
- An activity lifecycle
Example prompts
- “/heap-discipline”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Stack? Local, bounded, under ~256 bytes total: plain array/struct. No
- Compile-time constant? static constexpr lives in flash, costs zero DRAM.
- Allocated once and reused for an activity's lifetime? Allocate in
- Dynamic and fallible? makeUniqueNoThrow(...) /
- A C/SDK API takes ownership and frees it itself? Only then raw
What it can do on your machine
Read from SKILL.md and the folder at commit d272143. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Heap Discipline loads about 889 tokens when it runs. Until then it costs about 115 tokens; SKILL.md has 430 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from yokki-vans/InkPointX at commit d272143, republished under its MIT licence (© yokki-vans). 430 words, ~889 tokens.
Download SKILL.mdSave it as
.claude/skills/heap-discipline/SKILL.md (or your agent's skills folder).- name
- heap-discipline
- description
- Memory allocation discipline for the ESP32-C3 (~380KB RAM, no PSRAM, single 48KB framebuffer). Use whenever writing or reviewing code that allocates: new / malloc / std::vector / std::string, buffers, caches, or anything held across a loop or an activity lifecycle. Covers makeUniqueNoThrow vs raw new/malloc, fragmentation avoidance, reserve-before-push_back, alloc-once-reuse, stack vs heap sizing, and the chunked grayscale buffer pattern.
Heap Discipline (ESP32-C3)
CLAUDE.md states the allocation rules. This is the procedure you run while writing the code and the gate you run before handing it back.
The constraint that makes every call matter: ~380KB RAM, no PSRAM, one 48KB framebuffer. Fragmentation, not total usage, is what kills this device. Free-heap can read fine while the largest free block is too small for the next allocation. Optimize for not leaving holes, not just for using fewer bytes.
Allocation decision procedure
Ask in order; stop at the first yes.
- Stack? Local, bounded, under ~256 bytes total: plain array/struct. No heap, no fragmentation. Keep frames lean; the task stack is small.
- Compile-time constant?
static constexprlives in flash, costs zero DRAM. - Allocated once and reused for an activity's lifetime? Allocate in
onEnter, hold in a member, release inonExit. Never per-frame, never per-iteration. - Dynamic and fallible?
makeUniqueNoThrow<T>(...)/makeUniqueNoThrow<T[]>(n)fromlib/Memory/Memory.h. Null-check,LOG_ERRwith the size, return false. It frees on every exit path. - A C/SDK API takes ownership and frees it itself? Only then raw
new (std::nothrow)/malloc, with a comment naming who frees it.
Bare new / new[] is never correct here: under -fno-exceptions it calls
abort() on OOM instead of returning null.
Show full SKILL.md (224 more words)Show less
Fragmentation rules
std::vector:reserve(n)before anypush_backloop. Each growth is alloc-copy-free (three heap ops) and leaves a hole. Unknown n: estimate high.- No repeated
new/deleteor growing containers inside a loop or render path. Hoist the allocation out of the loop. - Large contiguous blocks fragment worst. Full-screen-class buffers use the
chunked
storeBwBuffer/restoreBwBufferpath inGfxRendererso they never demand one contiguous 48KB block. Reuse that path. Do not malloc a second full-screen buffer. std::string/ ArduinoString: acceptable on cold paths (file I/O, one-shot setup). Banned on hot/render paths. Build text with a stackchar[]+snprintf; if astd::stringis unavoidable,reserveit first.
Justify every allocation
Per CLAUDE.md's evidence rule: when you add a heap allocation, state in one line why stack/static/reuse was rejected and the worst-case size. If you cannot name the size, you cannot budget it, and you should not allocate it.
Self-review before handoff
- No bare
new/new[]. Every fallible alloc ismakeUniqueNoThrow, or a raw alloc with an explicit owner comment. - Every allocation is null-checked with
LOG_ERRbefore the error return. - No allocation inside a loop or render path that could be hoisted.
- Every
push_backloop has a precedingreserve. - Anything allocated in
onEnteris released inonExit; memberHalFileclosed there too. - No second full-screen buffer; grayscale uses store/restoreBwBuffer.
- Each new allocation carries a one-line size + why-not-stack/static note.
© yokki-vans, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in .claude/skills/heap-discipline of yokki-vans/InkPointX.
Open the folder on GitHubat commit d272143
Compare with similar skills
Heap Discipline next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Heap Discipline this skillyokki-vans/InkPointX | 107 | — | ~889 | Automated safety check: Pass | MIT | |
| RuView Hardware Setupruvnet/RuView | 97k | — | ~1.8k | Automated safety check: Notes | MIT | |
| Esp32 Firmware Engineeralxv2016/folloup-sticky | 117 | 1 repos | ~3.8k | Automated safety check: Pass | GPL-3.0 | |
| RuView mmWave Radar Setupruvnet/RuView | 97k | — | ~907 | Automated safety check: Notes | MIT | |
| Embedded DebugFastLED/FastLED | 7.5k | — | ~1.4k | Automated safety check: Pass | MIT | |
| Auto EmbeddedDunCanYounG-1/MICU-auto-embedded | 253 | — | ~1.6k | Automated safety check: Pass | CC-BY-NC-4.0 |
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Related
Works with
Categories
Questions about Heap Discipline
What does Heap Discipline do?
Memory allocation discipline for the ESP32-C3 (~380KB RAM, no PSRAM, single 48KB framebuffer). Heap Discipline is an agent skill from yokki-vans/InkPointX. Memory allocation discipline for the ESP32-C3 (~380KB RAM, no PSRAM, single 48KB framebuffer).
When should I use Heap Discipline?
Heap Discipline fits situations like: reviewing code that allocates: new / malloc / std::vector / std::string; anything held across a loop; an activity lifecycle.
How do I install Heap Discipline in Claude Code?
Run `npx skills add yokki-vans/InkPointX --skill heap-discipline -a claude-code`. Or copy the skill folder (.claude/skills/heap-discipline in yokki-vans/InkPointX) into .claude/skills/heap-discipline in your project. Claude Code loads it when a task matches its description.
How do I install Heap Discipline in Codex?
Run `npx skills add yokki-vans/InkPointX --skill heap-discipline -a codex`. Or copy the skill folder (.claude/skills/heap-discipline in yokki-vans/InkPointX) into .agents/skills/heap-discipline in your project. Codex loads it when a task matches its description.
Can I use Heap Discipline in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add yokki-vans/InkPointX --skill heap-discipline -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/heap-discipline, .gemini/skills/heap-discipline, .github/skills/heap-discipline and .opencode/skills/heap-discipline in your project.
What does Heap Discipline need to run?
SKILL.md names no scripts, command-line tools or credentials: Heap Discipline is instructions for the agent only.
Does Heap Discipline access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Heap Discipline safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Heap Discipline use?
Heap Discipline is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Heap Discipline use?
About 889 tokens (SKILL.md is roughly 3.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Heap Discipline?
Skills that share tags, products or a category with Heap Discipline: RuView Hardware Setup (ruvnet/RuView, 97k stars), Esp32 Firmware Engineer (alxv2016/folloup-sticky, 117 stars), RuView mmWave Radar Setup (ruvnet/RuView, 97k stars) and Embedded Debug (FastLED/FastLED, 7.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Heap Discipline?
yokki-vans (a GitHub user) maintains it in yokki-vans/InkPointX, which has 107 GitHub stars. The repository holds 5 skills in this directory. The repository was last updated on September 24, 2026.
Source: yokki-vans/InkPointX on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.