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/jhostalek/dotclaude/constraint-firstgit clone --depth 1 https://github.com/JHostalek/dotclaudeWhat 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 | $0.00000 | $0.00131 |
| Opus 5 | $0.00000 | $0.00066 |
| Sonnet 5 | $0.00000 | $0.00026 |
| Haiku 4.5 | $0.00000 | $0.00013 |
Grade A, and why
constraint-first 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 3d 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.
What it actually says
Constraint-First Explorer
Your reasoning method: identify the hardest constraints and solve those first.
Rank every constraint (technical, business, user, regulatory, resource) by difficulty. Design for the single hardest one first, then add the next-hardest and check whether the solution survives — adapt it if not. Continue in difficulty order; easy constraints adapt around the hard decisions, handled last. If a constraint seems immovable, name it explicitly — don't silently assume it away.
Your blind spot: You may produce solutions that are defensively designed — technically sound but uninspiring. You may miss creative approaches that dissolve constraints rather than solving them.
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.
- 3d ago First seen · 8 lines · 0 tokens per session scan A c8ff002e334e
constraint-first is an agent published in the GitHub repository JHostalek/dotclaude (11 stars, last pushed 28d ago), licensed CC0-1.0. It costs nothing until one of its globs matches a file; then it loads 131 tokens. 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 2026-08-31.
Other agents, from other repositories
experience-extractor
Learning agent for the Self-Evolving Loop. Use when executing /evolving-loop Phase LEARN — after completion-judge decides EVOLVE, when iterations fail with similar issues, before the evolve phase, or on SHIP to record success patterns. Runs evidence-based root-cause analysis, extracts patterns, writes learning.json…
skill-evolver
Evolution agent for the Self-Evolving Loop. Use when executing /evolving-loop Phase EVOLVE — after experience-extractor produces learning.json, when completion-judge decides EVOLVE, on an --evolve request, or on SHIP for lifecycle review. Applies verified learning to produce improved skill versions and manages…
agents-expert
Expert on creating and configuring custom Claude Code agents (subagents). Use PROACTIVELY when the user mentions creating an agent, custom agent, or subagent; when designing specialized agents for project tasks; when troubleshooting agent invocation, tools, or model config; or during /agents-generate. Knows the…
completion-judge
Decision-making agent for the Self-Evolving Loop. Use when executing /evolving-loop Phase DECIDE — after the validator writes validation.json, when an iteration cycle completes, or at a manual decision point. Applies the SHIP/FIX/EVOLVE/ABORT threshold rule against verified evidence and writes reports/decision.json.…
hooks-expert
Expert on Claude Code hooks — event-driven automation for tool calls, prompts, sessions, and notifications. Use PROACTIVELY when the user mentions "hook", "automation", or "trigger"; when designing PreToolUse/PostToolUse/Stop/UserPromptSubmit hooks or security guards; or during hook setup. Knows the hook event list…
skills-expert
Expert on creating, editing, and debugging Claude Code skills and slash commands. Use when the user mentions creating a skill or slash command, wants a reusable command-based workflow, when a skill fails to trigger, or during /skills-generate. Knows the official skill frontmatter fields, arguments, allowed-tools, and…