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 spinningrachel/career-engine --skill content-orchestratorgit clone --depth 1 https://github.com/spinningrachel/career-engineWrote 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/spinningrachel/career-engine/content-orchestrator)<a href="https://agentmods.dev/skills/spinningrachel/career-engine/content-orchestrator"><img src="https://agentmods.dev/badge/skills/spinningrachel/career-engine/content-orchestrator/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/spinningrachel/career-engine/content-orchestrator"><img src="https://agentmods.dev/badge/skills/spinningrachel/career-engine/content-orchestrator.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 | $0.00026 | $0.00901 |
| Opus 5 | $0.00013 | $0.00451 |
| Sonnet 5 | $0.00005 | $0.00180 |
| Haiku 4.5 | $0.00003 | $0.00090 |
Grade A, and why
content-orchestrator 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Orchestrator Skill
Format Mix
The target mix ensures the content calendar doesn't become monotone. A feed of all Format A posts is dense and exhausting; all Format C posts signals a lack of depth. The mix keeps variety visible to followers.
Target: ~50% Format A / ~30% Format B / ~20% Format C
This is a target, not a hard constraint. Apply it across a batch of 3–5 posts. For a batch of 3:
- Ideal: 2A + 1B, or 1A + 1B + 1C
- Acceptable: 2A + 1C, or 1A + 2B
- Avoid: 3A (too dense), 3C (too thin), 2C + 1A (imbalanced)
For a batch of 5:
- Ideal: 2A + 2B + 1C, or 3A + 1B + 1C
- Avoid: 4A + 1C, or 3C + 2B
Format assignment by idea content:
- Assign Format A when the idea has a repeatable model or framework with 2+ real proof points — check the idea's Summary and Raw Notes before assigning
- Assign Format B when the idea is a sharp observation with one real example or scenario
- Assign Format C when the idea is procedural, tool-specific, or step-by-step
If the mix of available ideas doesn't support the target (e.g., all ideas are Format A candidates), note this in the batch proposal and proceed with the available formats rather than force-assigning the wrong format.
Batch Selection Criteria
When selecting which ideas to include in a batch:
-
Prefer ideas with fuller Raw Notes. An idea with detailed notes produces a better post than one with a bare title. The Summary and Raw Notes fields are the evidence — if they're thin, flag the idea as "needs development" rather than including it.
-
Topic variety within a batch. Avoid two ideas from the same Topic Authority Area in the same batch. Readers see the whole batch over a few days — topic monotony is visible. Refer to
${CAREER_DATA}/references/voice-and-identity/linkedin-post-strategy.mdfor the authority areas. -
Category distribution. Don't run a batch of all
LinkedIn Postcategory ideas ifContent FrameworkorPersonal Experienceideas are available — different categories produce different post textures.
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 · 68 lines · 26 tokens per session scan A 69d8475dbf3c
content-orchestrator is a skill published in the GitHub repository spinningrachel/career-engine (4 stars, last pushed 28d ago), licensed MIT. It adds 26 tokens to every session and 901 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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