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Ape Write Pseudocode

Community
arpitbbhayani
ape-write-pseudocode

Guidelines for writing pseudocode for functions and algorithms. Use this skill whenever the user asks to write pseudocode, sketch out an algorithm, or describe the logic of a function at a high level. Trigger on phrases like "write pseudocode", "sketch this algorithm", "pseudocode for this function", or "describe the logic".

Overview

Publisherarpitbbhayani
Repositoryape-skills
Skill nameape-write-pseudocode
Stars
51
Forks
5
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by arpitbbhayani on GitHub. Read the source before you install it.

Installation

Install the Ape Write Pseudocode AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/arpitbbhayani/ape-skills/tree/master/ape-write-pseudocode
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/arpitbbhayani/ape-skills.git /tmp/ape-skills
mkdir -p .claude/skills
cp -r /tmp/ape-skills/ape-write-pseudocode .claude/skills/ape-write-pseudocode
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ape Write Pseudocode in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ape Write Pseudocode on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ape Write Pseudocode is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Pseudocode Style Guide

Structure of a Function

Every pseudocode function has exactly three parts: input, output, and body. Use Python-like syntax: def for the function signature, a docstring-style comment block for input and output, and indented body lines.

def function_name(param1, param2, ...):
    # input:  <what each param represents>
    # output: <what the function returns or produces>

    <body>

Body Rules

The body is the core of the pseudocode. Each line is a pythonic, non-functional call that names the operation and its operands -- not English prose. Invent clear, intuitive method or function names. The goal is code that reads like intent, not implementation.

  • One call per logical step.
  • Use object.verb(args) or verb(args) style -- never English sentences.
  • No type annotations, no real data-structure internals, no language-specific APIs.
  • Intermediate variable names are fine when they connect two steps.
  • Never more than one idea per line.

Control Flow

Use if, elif, else, and loops sparingly and only when the branching or iteration is the point of the logic. Conditions are also written as code-like expressions, not prose.

if condition_call(args):
    ...
else:
    ...

for item in collection:
    ...

while not done():
    ...

What to Write on Each Line

Each line should look like a call you would recognise but cannot actually run.

Good patterns:

  • nodes.filter_reachable_from(source)
  • entries.sort_by(timestamp, order=ASC)
  • graph.shortest_path(source)
  • candidates.pick_highest_score()
  • merge_sorted(left, right)

Bad patterns:

  • "filter nodes by reachability from source" -- English sentence, not code
  • dist[v] = dist[u] + weight(u, v) -- actual implementation code
  • initialize a min-heap priority queue with (0, source) -- prose + detail
  • list.stream().filter(x -> x > 0).collect(...) -- real language API

Examples

Good:

python
def lsm_write(key, value):
    # input:  key and value to store
    # output: acknowledgement that write is recorded

    memtable.append(key, value)
    if memtable.exceeds_threshold():
        sstable = memtable.flush_to_disk()
        memtable.clear()
python
def lsm_read(key):
    # input:  key to look up
    # output: value for key, or NOT_FOUND

    if memtable.contains(key):
        return memtable.get(key)
    for sstable in sstables.newest_first():
        if sstable.bloom_filter.might_contain(key):
            value = sstable.search(key)
            if value:
                return value
    return NOT_FOUND
python
def lsm_compact(sstables):
    # input:  list of SSTables to merge
    # output: single merged SSTable with duplicates resolved

    cursors = sstables.open_cursors()
    while cursors.any_remaining():
        entry = cursors.pick_min_key()
        if cursors.has_duplicates(entry.key):
            entry = cursors.keep_newest(entry.key)
        output.write(entry)
    return output.finalise()

Bad (do not do this):

python
def lsm_write(key, value):
    append key-value pair to memtable          # English sentence -- wrong
    if memtable exceeds size threshold:        # English condition -- wrong
        flush memtable to a new SSTable        # English sentence -- wrong
python
def lsm_write(key: str, value: bytes):  # typed signature + real Python -- wrong
    self.lock.acquire()
    self.memtable[key] = value
    if len(self.memtable) > self.threshold:
        self.flush()
    self.lock.release()

Checklist Before Writing

  • Are all body lines calls (object.verb(args) or verb(args)), not English sentences?
  • Are invented names intuitive -- would a reader guess what they do?
  • Are if/else conditions also written as calls or simple expressions, not prose?
  • Is every line a single idea?

If yes, the pseudocode is done.

Frequently asked questions

What does the Ape Write Pseudocode AI skill do?

Guidelines for writing pseudocode for functions and algorithms. Use this skill whenever the user asks to write pseudocode, sketch out an algorithm, or describe the logic of a function at a high level. Trigger on phrases like "write pseudocode", "sketch this algorithm", "pseudocode for this function", or "describe the logic".

Why use Ape Write Pseudocode on TypingMind?

Because you install it once and use it with any model. Ape Write Pseudocode is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ape Write Pseudocode in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/arpitbbhayani/ape-skills/tree/master/ape-write-pseudocode. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ape Write Pseudocode?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ape Write Pseudocode?

As many as you like. As long as a model supports skills, you can use Ape Write Pseudocode with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ape Write Pseudocode AI skill free?

Yes. It is published on GitHub by arpitbbhayani under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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