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 categories-functorsgit 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/categories-functors)<a href="https://agentmods.dev/skills/parcadei/continuous-claude-v3/categories-functors"><img src="https://agentmods.dev/badge/skills/parcadei/continuous-claude-v3/categories-functors/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/categories-functors"><img src="https://agentmods.dev/badge/skills/parcadei/continuous-claude-v3/categories-functors.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 43 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 65 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 | $0.00015 | $0.00559 |
| Opus 5 | $0.00008 | $0.00280 |
| Sonnet 5 | $0.00003 | $0.00112 |
| Haiku 4.5 | $0.00002 | $0.00056 |
Grade A, and why
categories-functors 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
Categories Functors
When to Use
Use this skill when working on categories-functors problems in category theory.
Decision Tree
-
Verify Category Axioms
- Objects and morphisms (arrows) defined?
- Identity morphism for each object: id_A: A -> A
- Composition associative: (f . g) . h = f . (g . h)
- Write Lean 4:
theorem assoc : (f ≫ g) ≫ h = f ≫ (g ≫ h) := Category.assoc
-
Check Functor Properties
- F: C -> D maps objects to objects, arrows to arrows
- Preserves identity: F(id_A) = id_{F(A)}
- Preserves composition: F(g . f) = F(g) . F(f)
- Write Lean 4:
theorem comp : F.map (g ≫ f) = F.map g ≫ F.map f := F.map_comp
-
Functor Types
- Covariant: preserves arrow direction
- Contravariant: reverses arrow direction
- Faithful/Full: injective/surjective on Hom-sets
- Equivalence: full, faithful, essentially surjective
-
Common Functors
- Forgetful functor: forgets structure (e.g., Grp -> Set)
- Free functor: left adjoint to forgetful
- Hom functor: Hom(A, -) or Hom(-, B)
- Power set functor: Set -> Set via X |-> P(X)
-
Verify with Lean 4
- Compiler-in-the-loop: write proof,
lake buildchecks - Mathlib has full category theory library
- See:
.claude/skills/lean4-functors/SKILL.mdfor exact syntax
- Compiler-in-the-loop: write proof,
Tool Commands
Lean4_Category
# Lean 4 with Mathlib: import CategoryTheory.Category.Basic
Lean4_Functor
# Lean 4: theorem map_comp (F : C ⥤ D) : F.map (g ≫ f) = F.map g ≫ F.map f := F.map_comp
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 · 66 lines · 15 tokens per session scan A be2ae6a09d47
categories-functors is a skill published in the GitHub repository parcadei/Continuous-Claude-v3 (3,938 stars, last pushed 7mo ago), licensed MIT. It adds 15 tokens to every session and 559 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.
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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…
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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.