Borrowing it
Nothing to install: this file belongs to hashangit/openfusion. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/hashangit/openfusion/main/.agents/skills/management-talk/SKILL.mdgit clone --depth 1 https://github.com/hashangit/openfusionWrote 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/hashangit/openfusion/management-talk)<a href="https://agentmods.dev/skills/hashangit/openfusion/management-talk"><img src="https://agentmods.dev/badge/skills/hashangit/openfusion/management-talk/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/hashangit/openfusion/management-talk"><img src="https://agentmods.dev/badge/skills/hashangit/openfusion/management-talk.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 | $0.00136 | $0.03138 |
| Opus 5.5 | $0.00054 | $0.01255 |
| Sonnet 5.5 | $0.00027 | $0.00628 |
| Haiku 4.5 | $0.00014 | $0.00314 |
Grade A, and why
management-talk 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 2mo 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Management Talk
Same audience and translation rules as a written status report, but shaped for the channel — JIRA comment, Slack post, async standup, email, or meeting talking-points. The audience reads code names but not code. The channel decides the length, formatting, and how much structure to leave on the page.
Use this any time engineering content needs to flow up the org, sideways into product/release, or into a non-engineering meeting — regardless of the destination.
When to invoke
- "write something for management / exec / VP / director / PM / release manager"
- "rewrite this for [non-eng audience]"
- "make this non-technical" / "less techy" / "less jargony"
- "send a slack update / standup note / email" about a piece of engineering work
- "executive summary" / "exec summary" / "leadership update" / "status update"
- "talking points for [meeting]" based on an engineering update
If the channel is unclear after the trigger, ask one short question — "JIRA, Slack, standup, or email?" — and stop.
Audience — what "engineering-org leadership" means
Engineering-savvy non-engineers: VPs, directors, PMs, release managers, execs in companies that ship technical products. They read product/framework names and cross-reference JIRA keys and PRs. They do not read code.
They want: what's the state, what does it mean for customers, who owns it, what's next. They do not want: how the bug works at the function level.
This is not for marketing, finance, customer-facing, or true ELI5 audiences — those need a different rewrite. Flag and confirm before producing one.
Tone
Keep. Product names, framework names, team-owned component names, JIRA keys, PR numbers, customer/workload identifiers (Tada, DeepSpeed, PyTorch, Llama-2-70B, vLLM, JIRA-12345, PR #5751). These are the bridge between engineering and leadership tracking.
Strip. Function names, file paths, struct fields, commit SHAs, code expressions, env var names, line numbers, internal data-structure jargon (tadaLaunchPrepare, tada/prim.h::syncWaitPeer, scratchBuf, 0e0a6bac). None of this is actionable to the audience.
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.
- 2mo ago First seen · 174 lines · 136 tokens per session scan A 10e4aa927878
management-talk is a skill published in the GitHub repository hashangit/openfusion (35 stars, last pushed 3d ago), licensed MIT. It adds 136 tokens to every session and 3,138 once invoked, about $0.0005 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 2026-08-30.
management-talk compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| management-talkhashangit/openfusion | Skill | 35 | 3d ago | MIT | A | 136 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 103 | Claude Code |