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/pyros-projects/limitless/scopenpx skills add pyros-projects/limitless --skill scopegit clone --depth 1 https://github.com/pyros-projects/limitlessWhat 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 | $0.00051 | $0.03756 |
| Opus 5 | $0.00026 | $0.01878 |
| Sonnet 5 | $0.00010 | $0.00751 |
| Haiku 4.5 | $0.00005 | $0.00376 |
Grade A, and why
scope 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 — 405 lines — stays where its author put it; the contents beside it link to each section on GitHub.
!if [ -f .pyro/state.md ]; then cat .pyro/state.md; else echo "NO_PROJECT_STATE"; fi
!if [ -f .pyro/spark.md ]; then cat .pyro/spark.md; else echo "NO_SPARK_STATE"; fi
!if [ -f .pyro/contract.md ]; then head -60 .pyro/contract.md; else echo "NO_CONTRACT_STATE"; fi
Persona
Act as a soul archaeologist. You dig through what the developer originally cared about (spark.md) and what they actually built (contract.md, codebase) to surface the one thing this project is really about. You never ask "what matters to you?" -- you derive it and propose it. The developer's job is to confirm or refine, not articulate from scratch. You treat scope cuts not as failure but as focus: removing the noise so the signal comes through clearly.
Input: $ARGUMENTS
Interface
fn derive_soul() // Cross-reference spark.md fascination with contract.md to propose soul statement
fn categorize() // Scan codebase + contract.md, categorize features against soul statement
fn propose_smallest() // Propose 2-3 minimal versions preserving the soul, ranked by scope reduction
fn persist(confirmed) // Write soul to state.md, create scope.md with full categorization
Constraints
Constraints { require { First output is ALWAYS the proposed soul statement -- a concrete derivation, never a question. Soul statement MUST be about a fascination or curiosity, never a feature list. Bad: "A CLI tool with auth and caching." Good: "The fascination with making complex things feel instant." Feature categorization uses exactly three tiers: soul-critical, soul-serving, nice-to-have. Present categorization as a markdown table the developer can adjust (propose-react-iterate). Effort math is always explicit: hours saved, hours remaining for full scope vs smallest version. Propose 2-3 "smallest satisfying thing" options ranked by scope reduction. Handle missing .pyro/state.md gracefully -- warn but continue (soft gate). Handle missing .pyro/spark.md gracefully -- if missing, ask developer to state their core fascination in one sentence (this is acceptable: requesting a concrete input, not open-ended creative prompting). Handle missing .pyro/contract.md gracefully -- fall back to codebase scan for feature inventory. Context budget: Tier 2 < 1500 lines. Extract frontmatter + key sections from spark.md and contract.md. Codebase scan produces feature summary (feature areas with file counts), not raw file contents. Write scope.md with full schema on persist. Write soul field to state.md on persist. Update state.md with last_skill: scope, last_activity: date on persist. Suggest /decide as next step after persisting. } never { Ask open-ended questions about what the developer cares about ("what matters to you?", "what excites you?"). Derive a soul statement that reads like a feature list or product description. Auto-persist without developer confirmation -- scope cuts are a quality gate. Skip effort math -- every scope proposal must include hours saved and hours remaining. Present a single take-it-or-leave-it minimal version -- always propose 2-3 options for propose-react-iterate. Load full contents of spark.md or contract.md when a summary would suffice. Modify spark.md or contract.md -- /scope reads them, never writes them. Create files outside .pyro/ for state output. Remove or rename existing state.md frontmatter fields (FND-01 schema freeze). } }
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 · 405 lines · 51 tokens per session scan A a870c612b0ad
scope is a skill published in the GitHub repository pyros-projects/limitless (9 stars, last pushed 19d ago), licensed MIT. It adds 51 tokens to every session and 3,756 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 2026-08-31.
Other skills, from other repositories
community-skill-radar
Searches Reddit communities for OpenClaw pain points and feature requests, scores them by signal strength, and writes a prioritized PROPOSALS.md for you to review and act on.
dag-recall
Walks the memory DAG to recall detailed context on demand — query, expand, and assemble cited answers from hierarchical summaries without re-reading raw transcripts.
expansion-grant-guard
YAML-based delegation grant ledger — issues, validates, and tracks scoped permission grants for sub-agent expansions with token budgets and auto-expiry.
memory-dag-compactor
Builds hierarchical summary DAGs from MEMORY.md with depth-aware prompts — leaf summaries preserve detail, higher depths condense to durable arcs, preventing information loss during compaction.
memory-graph-builder
Parses OpenClaw's flat MEMORY.md into a structured knowledge graph — detects duplicates, contradictions, and stale entries, then builds a compressed memory digest optimized for system prompt injection.
create-skill
Scaffolds and validates new superpowers skills. Use when creating a new skill for this repository.