Continuous-Claude-v3 is a Claude Code development environment that preserves working context between sessions, coordinates specialized agents, and stores project knowledge through ledgers, handoffs, and analysis tools. It is for people using Claude Code on ongoing or complex software work. Its catalogue entries are the skills, agents, hooks, plugin, and setting that provide its workflows and orchestration.
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 skills add parcadei/Continuous-Claude-v3 --skill limits-colimitsgit clone --depth 1 https://github.com/parcadei/Continuous-Claude-v3Wrote 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/parcadei/continuous-claude-v3/limits-colimits)<a href="https://agentmods.dev/skills/parcadei/continuous-claude-v3/limits-colimits"><img src="https://agentmods.dev/badge/skills/parcadei/continuous-claude-v3/limits-colimits/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/parcadei/continuous-claude-v3/limits-colimits"><img src="https://agentmods.dev/badge/skills/parcadei/continuous-claude-v3/limits-colimits.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 46 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 73 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 5.1 | $0.00014 | $0.00533 |
| Opus 5 | $0.00007 | $0.00267 |
| Sonnet 5 | $0.00003 | $0.00107 |
| Haiku 4.5 | $0.00001 | $0.00053 |
Grade A, and why
limits-colimits 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 9d 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
Limits Colimits
When to Use
Use this skill when working on limits-colimits problems in category theory.
Decision Tree
-
Identify Limit Type
- Product: limit of discrete diagram
- Equalizer: limit of parallel pair f, g: A -> B
- Pullback: limit of A -> C <- B
- Terminal object: limit of empty diagram
- Lean 4:
CategoryTheory.Limitsnamespace
-
Verify Universal Property
- Cone from L with projections pi_i: L -> D_i
- For any cone from X, unique morphism u: X -> L
- Triangles commute: pi_i . u = cone_i
- Lean 4:
IsLimit.liftgives the unique morphism
-
Colimit (Dual)
- Coproduct: colimit of discrete diagram
- Coequalizer: colimit of parallel pair
- Pushout: colimit of A <- C -> B
- Initial object: colimit of empty diagram
-
Compute Limits Concretely
- In Set: product = Cartesian product
- Equalizer = {x | f(x) = g(x)}
- Pullback = {(a,b) | f(a) = g(b)}
sympy_compute.py solve "f(a) == g(b)"
-
Preservation
- Right adjoint preserves limits
- Left adjoint preserves colimits
- Representable functors preserve limits
- Lean 4:
Adjunction.rightAdjointPreservesLimits - See:
.claude/skills/lean4-limits/SKILL.mdfor exact syntax
Tool Commands
Lean4_Limit
# Lean 4: import CategoryTheory.Limits.Shapes.Products
Lean4_Universal
# Lean 4: IsLimit.lift cone -- unique morphism from universal property
Sympy_Pullback
uv run python -m runtime.harness scripts/sympy_compute.py solve "f(a) == g(b)"
Lean4_Build
lake build # Compiler-in-the-loop verification
Cognitive Tools Reference
See .claude/skills/math-mode/SKILL.md for full tool documentation.
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.
- 9d ago First seen · 74 lines · 14 tokens per session scan A 7c0298572cee
limits-colimits is a skill published in the GitHub repository parcadei/Continuous-Claude-v3 (3,938 stars, last pushed 7mo ago), licensed MIT. It adds 14 tokens to every session and 533 once invoked, about $0.0001 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 2026-09-03.
Other skills, from other repositories
explain-it
Explain technical concepts, mechanisms, and systems to a technically fluent reader who is unfamiliar with the specific topic. Use when asked to explain how something works, walk through an algorithm or protocol, write a deep-dive or onboarding article, answer 'what is X', 'why does X behave this way', 'how does X…
process
CORE learning workflow — use this whenever the user has a source note open (paper, post, book, lecture, course, clipping) and wants to extract knowledge, understand what they just read, or build it into their vault. Triggers on "process this note", "process this paper", "extract concepts", "what can I learn from…
recall
Spaced repetition and retrieval practice engine for the vault. Use when the user wants a review session, recall practice, to test what they remember, or to resurface notes. Triggers on "review session", "what should I review", "recall practice", "resurface notes", "spaced repetition", "quiz me", "what do I know…
lecture
Extract transcript and key slides from a local video file, then create a vault-formatted lecture note. Use this skill whenever a user provides a local video file (.mp4, .mov, .mkv, .avi, .webm) and wants notes from it. Triggers on "lecture", "take notes", "I have a recording of", "class video", "transcribe this…
book-analyzer
Analyze a book (EPUB/PDF) and generate detailed chapter-by-chapter notes with extracted key concepts. Use when given a book file path to process.
fizzy-workflow
Use for guided Fizzy.do workflows: "set up Fizzy", "configure Fizzy for this project", "sync my work to Fizzy", "review my Fizzy progress", "end of session cleanup". Provides step-by-step guidance for common operations.