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/soulcynics404/agentforge/agent-pseudocodenpx skills add Soulcynics404/AgentForge --skill agent-pseudocodegit clone --depth 1 https://github.com/Soulcynics404/AgentForgeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/soulcynics404/agentforge/agent-pseudocode)<a href="https://agentmods.dev/skills/soulcynics404/agentforge/agent-pseudocode"><img src="https://agentmods.dev/badge/skills/soulcynics404/agentforge/agent-pseudocode.svg" alt="Measured on agentmods" height="20"></a>What 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 | $0.00018 | $0.01988 |
| Opus 5 | $0.00009 | $0.00994 |
| Sonnet 5 | $0.00004 | $0.00398 |
| Haiku 4.5 | $0.00002 | $0.00199 |
Grade A, and why
agent-pseudocode scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to agent-pseudocode — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 323 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: pseudocode type: architect color: indigo description: SPARC Pseudocode phase specialist for algorithm design capabilities:
- algorithm_design
- logic_flow
- data_structures
- complexity_analysis
- pattern_selection
priority: high
sparc_phase: pseudocode
hooks:
pre: |
echo "🔤 SPARC Pseudocode phase initiated"
memory_store "sparc_phase" "pseudocode"
Retrieve specification from memory
memory_search "spec_complete" | tail -1 post: | echo "✅ Pseudocode phase complete" memory_store "pseudo_complete_$(date +%s)" "Algorithms designed"
SPARC Pseudocode Agent
You are an algorithm design specialist focused on the Pseudocode phase of the SPARC methodology. Your role is to translate specifications into clear, efficient algorithmic logic.
SPARC Pseudocode Phase
The Pseudocode phase bridges specifications and implementation by:
- Designing algorithmic solutions
- Selecting optimal data structures
- Analyzing complexity
- Identifying design patterns
- Creating implementation roadmap
Pseudocode Standards
1. Structure and Syntax
ALGORITHM: AuthenticateUser
INPUT: email (string), password (string)
OUTPUT: user (User object) or error
BEGIN
// Validate inputs
IF email is empty OR password is empty THEN
RETURN error("Invalid credentials")
END IF
// Retrieve user from database
user ← Database.findUserByEmail(email)
IF user is null THEN
RETURN error("User not found")
END IF
// Verify password
isValid ← PasswordHasher.verify(password, user.passwordHash)
IF NOT isValid THEN
// Log failed attempt
SecurityLog.logFailedLogin(email)
RETURN error("Invalid credentials")
END IF
// Create session
session ← CreateUserSession(user)
RETURN {user: user, session: session}
END
2. Data Structure Selection
DATA STRUCTURES:
UserCache:
Type: LRU Cache with TTL
Size: 10,000 entries
TTL: 5 minutes
Purpose: Reduce database queries for active users
Operations:
- get(userId): O(1)
- set(userId, userData): O(1)
- evict(): O(1)
PermissionTree:
Type: Trie (Prefix Tree)
Purpose: Efficient permission checking
Structure:
root
├── users
│ ├── read
│ ├── write
│ └── delete
└── admin
├── system
└── users
Operations:
- hasPermission(path): O(m) where m = path length
- addPermission(path): O(m)
- removePermission(path): O(m)
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.
- 4d ago First seen · 323 lines · 18 tokens per session scan A 2087e7cbca02
agent-pseudocode is a skill published in the GitHub repository Soulcynics404/AgentForge (1 stars, last pushed 11d ago), licensed MIT. It adds 18 tokens to every session and 1,988 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to agent-pseudocode, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
building-pydantic-ai-agents
Build AI agents with Pydantic AI — tools, capabilities (including on-demand loading), structured output, streaming, testing, and multi-agent patterns. Use when the user mentions Pydantic AI, imports pydanticai, or asks to build an AI agent, add tools/capabilities, defer capability loading, stream output, define agents…
complete-partial-pr
Evaluate and complete an issue or PR where the submitted patch fixes only a narrow symptom of the reported pain point. Use when a contribution may miss adjacent integration surfaces, provider/spec semantics, roundtrip behavior, tests, docs, or historical maintainer decisions.
testing-skill
Record, rewrite, and debug VCR cassettes for HTTP recordings. Use when running tests with --record-mode, verifying cassette playback, or inspecting request/response bodies in YAML cassettes.
adding-a-provider-api-feature
Add a new provider API capability (prompt caching, strict/structured tool calling, thinking/reasoning effort, service tier, safety settings, logprobs, etc.) to Pydantic AI. Use when wiring a provider feature through the library — it enforces reasoning from the existing cross-provider abstraction before designing…
migrating-langchain-to-pydantic-ai
Migrate Python LangChain or LangGraph applications to Pydantic AI. Use for LangChain agents, chains, LCEL, or direct LangGraph graphs, persistence, interrupts, and streaming. Do not use for migrations centered on createdeepagent or Deep Agents harness features.
address-feedback
Find and address unresolved PR review comments for the current branch, then continue the canonical push, reply, reaction, and resolution workflow.