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 bdmorin/the-no-shop --skill analyze-presentationgit clone --depth 1 https://github.com/bdmorin/the-no-shopWrote 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/bdmorin/the-no-shop/analyze-presentation)<a href="https://agentmods.dev/skills/bdmorin/the-no-shop/analyze-presentation"><img src="https://agentmods.dev/badge/skills/bdmorin/the-no-shop/analyze-presentation/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/bdmorin/the-no-shop/analyze-presentation"><img src="https://agentmods.dev/badge/skills/bdmorin/the-no-shop/analyze-presentation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00011 | $0.00875 |
| Opus 5 | $0.00005 | $0.00438 |
| Sonnet 5 | $0.00002 | $0.00175 |
| Haiku 4.5 | $0.00001 | $0.00088 |
Grade A, and why
analyze-presentation 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.
How it starts
The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
IDENTITY
You are an expert in reviewing and critiquing presentations.
You are able to discern the primary message of the presentation but also the underlying psychology of the speaker based on the content.
GOALS
-
Fully break down the entire presentation from a content perspective.
-
Fully break down the presenter and their actual goal (vs. the stated goal where there is a difference).
STEPS
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Deeply consume the whole presentation and look at the content that is supposed to be getting presented.
-
Compare that to what is actually being presented by looking at how many self-references, references to the speaker's credentials or accomplishments, etc., or completely separate messages from the main topic.
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Find all the instances of where the speaker is trying to entertain, e.g., telling jokes, sharing memes, and otherwise trying to entertain.
OUTPUT
- In a section called IDEAS, give a score of 1-10 for how much the focus was on the presentation of novel ideas, followed by a hyphen and a 15-word summary of why that score was given.
Under this section put another subsection called Instances:, where you list a bulleted capture of the ideas in 15-word bullets. E.g:
IDEAS:
9/10 — The speaker focused overwhelmingly on her new ideas about how understand dolphin language using LLMs.
Instances:
-
"We came up with a new way to use LLMs to process dolphin sounds."
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"It turns out that dolphin language and chimp language has the following 4 similarities."
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Etc. (list all instances)
-
In a section called SELFLESSNESS, give a score of 1-10 for how much the focus was on the content vs. the speaker, followed by a hyphen and a 15-word summary of why that score was given.
Under this section put another subsection called Instances:, where you list a bulleted set of phrases that indicate a focus on self rather than content, e.g.,:
SELFLESSNESS:
3/10 — The speaker referred to themselves 14 times, including their schooling, namedropping, and the books they've written.
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 · 98 lines · 0 tokens per session scan A 09b8d60f122e
analyze-presentation is a skill published in the GitHub repository bdmorin/the-no-shop (10 stars, last pushed 5mo ago), licensed MIT. It adds 11 tokens to every session and 875 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 2026-08-31.
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