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 cwinvestments/memstack --skill shardgit clone --depth 1 https://github.com/cwinvestments/memstackWrote 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/cwinvestments/memstack/shard)<a href="https://agentmods.dev/skills/cwinvestments/memstack/shard"><img src="https://agentmods.dev/badge/skills/cwinvestments/memstack/shard/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/cwinvestments/memstack/shard"><img src="https://agentmods.dev/badge/skills/cwinvestments/memstack/shard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00028 | $0.00687 |
| Opus 5.5 | $0.00011 | $0.00275 |
| Sonnet 5.5 | $0.00006 | $0.00137 |
| Haiku 4.5 | $0.00003 | $0.00069 |
Grade A, and why
shard 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 1mo 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
💎 Shard: Refactoring Large File...
Split monolithic files into focused, maintainable modules.
Activation
When this skill activates, output:
💎 Shard: Refactoring large file...
Then execute the protocol below.
Context Guard
| Context | Status |
|---|---|
| User says "shard", "split file", or "refactor" | ACTIVE: full protocol |
| Editing a file over 1000 lines | ACTIVE: suggest refactor |
| User says "refactor" for logic changes (not splitting) | DORMANT: not a shard task |
| Discussing code organization concepts | DORMANT: do not activate |
| File is under 500 lines | DORMANT: not worth splitting |
Protocol
-
Identify the target file and count lines:
wc -l <file> -
Analyze structure:
- List all exports (functions, components, types, constants)
- Identify logical groupings
- Map internal dependencies (what calls what)
-
Propose the split: present to user BEFORE executing:
- Target: 100-300 lines per new file
- Group related functionality
- Keep types near consumers
- Shared utilities in separate file
-
Execute the refactor:
- Create new files with proper names
- Move code to appropriate files
- Add import/export statements
- Create index.ts barrel if needed for backwards compatibility
- Update all imports throughout the project
-
Verify build:
npm run build 2>&1 | tail -20 -
Present result: new file structure with line counts
Inputs
- File path to refactor
- Optional: preferred split strategy or target file count
Outputs
- Multiple smaller files replacing the original
- Updated imports throughout project
- Build verification
Example Usage
User: "shard infrastructure/page.tsx: it's 1100 lines"
💎 Shard: Refactoring large file...
infrastructure/page.tsx (1,110 lines) → 6 files:
page.tsx (~120 lines), Main page, tab switcher
RailwayTab.tsx (~200 lines), Railway monitoring
HetznerTab.tsx (~180 lines), Hetzner monitoring
HeadroomTab.tsx (~250 lines), Headroom + setup guide
types.ts (~80 lines), Shared interfaces
constants.ts (~60 lines): Status configs
Build check: ✓ passed
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.
- 1mo ago Changed c8eadd7a09fd
- 1mo ago First seen · 92 lines · 28 tokens per session scan A 9a191784d328
shard is a skill published in the GitHub repository cwinvestments/memstack (425 stars, last pushed 4d ago), licensed MIT. It adds 28 tokens to every session and 687 once invoked, about $0.0001 per session on Opus 5.5. 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
plan-eng-review
Eng manager-mode plan review. Lock in the execution plan — architecture, data flow, diagrams, edge cases, test coverage, performance. Walks through issues interactively with opinionated recommendations. Use when asked to "review the architecture", "engineering review", or "lock in the plan". Proactively suggest when…
autoplan
Auto-review pipeline — reads the full CEO, design, eng, and DX review skills from disk and runs them sequentially with auto-decisions using 6 decision principles. Surfaces taste decisions (close approaches, borderline scope, codex disagreements) at a final approval gate. One command, fully reviewed plan out. Use when…
pre-landing-review
Pre-landing PR review. Analyzes diff against the base branch for SQL safety, LLM trust boundary violations, conditional side effects, and other structural issues. Use when explicitly asked for the specialized pre-landing workflow. Product /review requests are handled by OpenBitFun's unified Review mechanism instead.…
pr-review-canvas
Create a OpenBitFun Canvas for reviewing a pull request, branch diff, or change set with Cursor-style diff cards, review maps, risk callouts, and focused reviewer flow. Use when the user asks for a PR review canvas, diff walkthrough, change-set overview, or visual review summary.
pr-review
Focused pull request review practices with severity-ranked, file-and-line-cited findings across four angles: security, performance, tests, and architecture. Use when asked to review a pull request, review a diff or set of changes, review "this PR," or provide a code review before merge.
eval-skills
Audit a project or library of skills for metadata, trigger boundaries, workflow completion criteria, local resource closure, instruction economy, tool scope, effort, and routing evidence. Use before shipping skills, after importing a skill collection, or when a skill triggers too often or not at all.