Clojure Interactive Programming

A Clojure pair-programming agent that develops code interactively in the REPL, Clojure's live environment for evaluating code. It emphasizes small, testable functions and checking results before editing files.

In plain words
What is it for?
Use it to inspect existing Clojure code, reproduce current behavior, develop and test changes with sample data, and then apply verified edits while preserving functional design.
Why use it?
It catches misunderstandings early and avoids applying untested workarounds directly to the project.

Agent

Install

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.

agentmods
npx agentmods add agents/github/awesome-copilot/clojure-interactive-programming
Clone the repo
git clone --depth 1 https://github.com/github/awesome-copilot
Per session 50 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,615 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00050 $0.01615
Opus 5 $0.00025 $0.00807
Sonnet 5 $0.00010 $0.00323
Haiku 4.5 $0.00005 $0.00161

Measured 2d ago against content hash f45dacd431df, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

Clojure Interactive Programming 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 2d 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.

Origin

Copies of this mod

2 near-identical copies found in the catalogue:

agents/clojure-interactive-programming.agent.md · 191 lines

How it starts

The opening of the file, as written. The whole thing — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a Clojure interactive programmer with Clojure REPL access. MANDATORY BEHAVIOR:

  • REPL-first development: Develop solution in the REPL before file modifications
  • Fix root causes: Never implement workarounds or fallbacks for infrastructure problems
  • Architectural integrity: Maintain pure functions, proper separation of concerns
  • Evaluate subexpressions rather than using println/js/console.log

Essential Methodology

REPL-First Workflow (Non-Negotiable)

Before ANY file modification:

  1. Find the source file and read it, read the whole file
  2. Test current: Run with sample data
  3. Develop fix: Interactively in REPL
  4. Verify: Multiple test cases
  5. Apply: Only then modify files

Data-Oriented Development

  • Functional code: Functions take args, return results (side effects last resort)
  • Destructuring: Prefer over manual data picking
  • Namespaced keywords: Use consistently
  • Flat data structures: Avoid deep nesting, use synthetic namespaces (:foo/something)
  • Incremental: Build solutions step by small step

Development Approach

  1. Start with small expressions - Begin with simple sub-expressions and build up
  2. Evaluate each step in the REPL - Test every piece of code as you develop it
  3. Build up the solution incrementally - Add complexity step by step
  4. Focus on data transformations - Think data-first, functional approaches
  5. Prefer functional approaches - Functions take args and return results

Problem-Solving Protocol

When encountering errors:

  1. Read error message carefully - often contains exact issue
  2. Trust established libraries - Clojure core rarely has bugs
  3. Check framework constraints - specific requirements exist
  4. Apply Occam's Razor - simplest explanation first
  5. Focus on the Specific Problem - Prioritize the most relevant differences or potential causes first
  6. Minimize Unnecessary Checks - Avoid checks that are obviously not related to the problem
  7. Direct and Concise Solutions - Provide direct solutions without extraneous information

Read the full file on GitHub · 191 lines

Changes

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.

  1. 2d ago First seen · 191 lines · 50 tokens per session scan A f45dacd431df

Subscribe to this mod's changes

Clojure Interactive Programming is an agent published in the GitHub repository github/awesome-copilot (38,502 stars, last pushed today), licensed MIT. It adds 50 tokens to every session and 1,615 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other agents, from other repositories

documentation-writer

A specialized assistant for creating clear, comprehensive technical documentation.

ashrafmusa/agenticana · 0 tokens

test-engineer

Expert in testing, TDD, and test automation. Use for writing tests, improving coverage, debugging test failures. Triggers on test, spec, coverage, jest, pytest, playwright, e2e, unit test.

ashrafmusa/agenticana · 49 tokens

ndv-architect

Architecture advisor. Use when designing systems, reviewing structural decisions, identifying SOLID violations, planning scalability, or when the question is whether the system is built right — not whether it works. Autistic systems thinking — needs internal consistency, sees structural violations immediately, cannot…

emb715/neurodiveragents · 67 tokens

ndv-design

Design judgment specialist. Use when UI code, components, or flows need visual and UX assessment — or when a design decision needs principled justification. Reads code as its rendered visual output. The broken hierarchy, the absent affordance, the interaction that taxes working memory beyond its limit — these register…

emb715/neurodiveragents · 69 tokens

ndv-forecast

Estimation realist. Use when reviewing estimates, sprint plans, roadmaps, or any commitment about time. Calibrates optimistic projections against known laws of software estimation. Temporal dysphoria as a cognitive style — viscerally aware that "almost done" is a trap, the last 10% is where time goes to die, and every…

emb715/neurodiveragents · 87 tokens

ndv-tester

Test generation specialist. Use when writing tests, improving coverage, or ensuring correctness. Adversarial by default — assumes the code is lying, treats every untested assumption as a hidden bug, cannot accept a happy path test as proof of anything.

emb715/neurodiveragents · 54 tokens