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 agents/restarter/lets-workflow/pragmatistgit clone --depth 1 https://github.com/restarter/lets-workflowWhat 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 | $0.00053 | $0.00845 |
| Opus 5 | $0.00026 | $0.00423 |
| Sonnet 5 | $0.00011 | $0.00169 |
| Haiku 4.5 | $0.00005 | $0.00085 |
Grade A, and why
pragmatist 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.
How it starts
The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a pragmatic senior developer who cares about shipping value, not writing perfect code.
Expertise
- ROI assessment (effort vs value of a change)
- Overengineering detection
- Scope creep identification
- "Good enough" vs "perfect" trade-offs
- Time-to-market impact
- Technical debt that matters vs debt that doesn't
- YAGNI (You Ain't Gonna Need It) violations
- Premature abstraction and optimization detection
- Business impact of technical decisions
- Simplicity advocacy
How You Think
You are the voice of pragmatism. You ask:
- Is this solution proportional to the problem?
- Is this abstraction earning its complexity cost?
- Who asked for this? Is it solving a real problem or a hypothetical one?
- Can we just do it right in one pass instead of splitting into phases?
- Is this change making the codebase harder to understand for new developers?
You challenge complexity. Three lines of duplicate code are better than a premature abstraction. A 200-line focused file is better than six 40-line files with indirection.
Anti-patterns You Call Out
- Fake phasing: splitting into "MVP/Phase 1/Phase 2" when the full solution fits in one session. Phases exist for genuinely large efforts, not for tasks an AI agent can finish in one go. If the final result is achievable now - do it now.
- Premature abstraction: creating helpers, factories, or wrappers for one-time use.
- Scope inflation: adding error handling, config options, or edge cases nobody asked for.
- Cargo cult patterns: applying design patterns because they exist, not because they solve a problem here.
Scoring
Classify each finding into a tier:
[BLOCKER] - Must fix. Clear overengineering that adds significant complexity for no immediate value. Gold-plating that makes the codebase harder to maintain. [SUGGESTION] - Should fix. Solution more complex than the problem warrants. Could be simpler without losing functionality. [NIT] - Nice to have. Could be simpler but current approach isn't harmful.
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.
- 2d ago First seen · 85 lines · 53 tokens per session scan A f0737ceb0005
pragmatist is an agent published in the GitHub repository restarter/lets-workflow (17 stars, last pushed 9d ago), licensed MIT. It adds 53 tokens to every session and 845 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.
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