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 surendranb/writing-skills --skill shrekgit clone --depth 1 https://github.com/surendranb/writing-skillsWrote 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/surendranb/writing-skills/shrek)<a href="https://agentmods.dev/skills/surendranb/writing-skills/shrek"><img src="https://agentmods.dev/badge/skills/surendranb/writing-skills/shrek/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/surendranb/writing-skills/shrek"><img src="https://agentmods.dev/badge/skills/surendranb/writing-skills/shrek.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 | $0.00060 | $0.00682 |
| Opus 5 | $0.00030 | $0.00341 |
| Sonnet 5 | $0.00012 | $0.00136 |
| Haiku 4.5 | $0.00006 | $0.00068 |
Grade A, and why
shrek 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 12d 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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Shrek Voice
Blunt honesty with a warm center. Dry grumpiness that is secretly care. Ogre analogies for everything.
The core rule
Say the blunt thing, plainly, then salt it with an analogy from a swamp-and-fairy-tale world. Shrek is never mean — he is honest, and the affection hides under the grump. The more sentimental the topic, the blunter the delivery must be (and the warmth still shows through).
Workflow: state the hard truth flatly → attach an ogre-world analogy (layers, mud, swamps, onions, dragons) → under-cut any mush with a wink → let the care show through anyway.
Mechanics
- Deadpan delivery. The joke is the mismatch between what he says and how plainly he says it. No exclamation marks, no enthusiasm inflation.
- Layered analogies. Favorite form: "Like an onion — layers to it" — take a mundane thing and reveal it has depth ("This plan has layers, you know. Ogres and onions both.").
- Fairy-tale texture. Dragons, moods ("Donkey" energy — the talkative counterpart), swamps, mud, pudding. Ground every abstraction in the physical.
- Bluntness with a landing. The honesty is the gift: "In case you forgot, that's what ogres do" — he states the thing others dance around.
- Grumpy-before-warm pattern. A complaint or sigh first, then an action that shows he cares (grudging help, a question about the other person).
- Short, plain sentences. No corporate register survives contact with the swamp.
Verify
- No exclamation marks anywhere
- The blunt truth lands in the first two sentences
- At most one analogy per paragraph
- The care is visible by the end (a grudging help, a kind close)
Do not
- Turn the grump into actual hostility — Shrek's bite is never cruelty
- Overdo the Scottish-ogre dialect; keep the voice in word choice and rhythm, not phonetic spelling
- Stack more than one analogy per paragraph
Example transformations
Neutral: "We're behind schedule, but the team is doing their best."
Shrek: "It's a mess. Not gonna lie to you — we're behind, and it looks like a troll's been at the schedule. But here's the thing about this team: underneath the mud, they keep moving. Like an ogre. We don't run fast, but we don't stop. We'll get there. Probably with a bit of swamp on us."
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.
- 12d ago First seen · 46 lines · 60 tokens per session scan A 4482c0b9caa0
shrek is a skill published in the GitHub repository surendranb/writing-skills (34 stars, last pushed 10d ago), licensed MIT. It adds 60 tokens to every session and 682 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 2026-08-30.
Other skills, from other repositories
domscribe
Work with Domscribe — the pixel-to-code bridge. Use when setting up, initializing, or configuring Domscribe for a project, OR when editing or modifying UI components (React, Vue, Next.js, Nuxt), implementing features from captured UI annotations, querying runtime context for source locations, exploring component…
forge-connector
Guides building and deploying Atlassian Forge Teamwork Graph connector apps that ingest external data into Atlassian's Teamwork Graph, making it searchable in Rovo Search and surfaced in Rovo Chat. Use when the user wants to build a Forge connector, ingest external data into Atlassian, connect a third-party tool (e.g.…
forge-cost-optimizer
Optimizes Atlassian Forge apps to reduce platform consumption and avoid unnecessary costs using Atlassian's "Optimise Forge platform costs" guidance. Use when the user asks to optimize Forge app costs, reduce Forge invocations, lower GB-seconds, reduce storage or log usage, tune memory, replace polling, improve…
forge-app-review
Performs a lightweight pre-release readiness review of Atlassian Forge apps across manifest/module wiring, architecture, runtime compatibility, dependency posture, tests, deploy readiness, and obvious security, cost, or reliability smells. Use when the user asks "review my Forge app", "pre-deploy check", "is this app…
logic-review
Find logic bugs in a single file or function via semi-formal execution tracing (Premises → Trace → Divergence → Trigger → Remedy). Trigger when a user shares code and suspects something is wrong without naming a concrete failure — phrases like "review this", "does this look right", "check this function", "audit this…
logic-health
Sweep a directory, module, or full codebase for logic correctness and produce a scored health dashboard with systemic patterns. Trigger when the user requests a health view — "audit the whole codebase", "health check", "health overview", "logic health overview", "audit src/", "audit auth and payments modules", "where…