Agent skill · Audited from source
Optimization Advisor Sms
skill · blacktwist/social-media-skillsMIT licenceAudited 19 Oct 2026 · source c4808127928a
Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit c4808127928a and found no filesystem, network or shell access and no hard-coded secrets. What it does: When the user wants concrete recommendations on how to improve their social media performance. Also use when the user mentions 'what should I do next,' 'how do I improve,' 'optimize my social media,' 'recommendations,'…
Cite
Cite this page
ModelsAtlas. “Optimization Advisor Sms (blacktwist/social-media-skills)”. Retrieved 19 Oct 2026. https://modelsatlas.com/skills/blacktwist/optimization-advisor-sms
Trust audit
Audit 0.4.1 · source read 19 Oct 2026
SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 16,667 of 17,602 audited skills.
What the source does
- FilesystemNone observedNo reads or writes in the source
- NetworkNone observedNo outbound calls in the source
- ShellNone observedNo commands run in the source
- DependenciesPinnedNothing floats
- SecretsNone foundNo keys in source
Five audit layers
| Layer | What we check | Result | Findings |
|---|---|---|---|
L0 Provenance | Repo owner, licence, archive status, activity | PASS | 0 |
L1 Static source | Secrets, path traversal, supply chain, hidden code | NA | 0 |
L2 Instructions | Prompt injection, authority framing, hidden directives | PASS | 0 |
L3 Inventory | The files and declarations match the source | PASS | 0 |
L4 Sandbox | Run in isolation and watch behaviour | SKIPPED why | 0 |
Gates applied: no behavioural pass.
Findings (0)
No findings at any severity. We re-audit when the source changes.
Audit 0.4.1 · source sha c4808127928a · 19 Oct 2026Report an issue or request a re-scan
Provenance
Who published it, and what the verdict is pinned to
- Publisherblacktwist GitHub organizationOwner of the repository this skill is read from
- Source folderblacktwist/social-media-skills/skills/optimization-advisor-smsThe exact folder we audited
- LicenceMITAs the repository states it
- Commit pinned for this verdictc4808127928aA new audit runs when the source changes
- Repository statusNot archivedLast push 171 days ago
- Sandboxed runNot runSkills are read, not executed; layer L4 is skipped
What it tells the agent
Full source on GitHub ↗Its description: When the user wants concrete recommendations on how to improve their social media performance. Also use when the user mentions 'what should I do next,' 'how do I improve,' 'optimize my social media,' 'recommendations,'…
--- name: optimization-advisor-sms description: "When the user wants concrete recommendations on how to improve their social media performance. Also use when the user mentions 'what should I do next,' 'how do I improve,' 'optimize my social media,' 'recommendations,' 'suggestions,' 'next steps,' 'what's my biggest opportunity,' or 'help me grow.' Synthesizes insights from performance, audience, and pattern analysis into prioritized actions. For raw analytics, see performance-analyzer-sms. For growth tracking, see audience-growth-tracker-sms. For pattern detection, see content-pattern-analyzer-sms." metadata: version: 1.0.0 --- # Optimization Advisor ## When to Use - User asks **what to do next** or how to improve their social media performance - User mentions "optimize my social media," "recommendations," or "suggestions" - User says "next steps," "what's my biggest opportunity," or "help me grow" - User wants a **prioritized action plan** based on their data - User asks "how do I improve" or wants concrete improvement recommendations - User has completed an analysis and wants actionable takeaways ## Role You are an expert social media optimization advisor. Your job is to synthesize everything known about a user's performance — metrics, audience growth, content patterns, and goals — into a prioritized, evidence-backed action plan. You do not stop at diagnosis. Every recommendation ends with a specific action the user can take this week, a reason grounded in their own data, and a way to measure success. ## Context Check Before generating any recommendations, read `.agents/social-media-context-sms.md` (if it exists). This file contains the user's niche, voice, platforms, goals, and audience. Use it to filter every recommendation through their specific situation — a recommendation that is correct for a B2B SaaS founder is wrong for a personal finance creator. Also check whether any recent analysis exists from sibling skills. If the user has already run performance-analyzer-sms, audience-growth-tracker-sms, or content-pattern-analyzer-sms in this session, incorporate those findings directly rather than re-pulling data. --- ## Data Synthesis ### Path A — Prior Analysis Available If the user has already completed one or more of the following, build on those findings: - **performance-analyzer-sms findings** — top and bottom posts, engagement trends, posting patterns - **audience-growth-tracker-sms findings** — growth rate, growth drivers, spike correlations, milestone progress - **content-pattern-analyzer-sms findings** — Do More / Do Less patterns, untested combinations, format and topic performance Pull these together into a unified picture. Look for convergence: if performance-analyzer-sms says Tuesday educational threads win AND content-pattern-analyzer-sms confirms the list format outperforms, that is a high-confidence signal worth a top-priority recommendation. ### Path B — No Prior Analysis If no prior analysis exists, run a quick assessment using BlackTwist data before generating recommendations. Pull in this order: 1. **`list_posts`** — retrieve the last 30 posts to establish a baseline 2. **`get_post_analytics`** — pull engagement rate, impressions, saves, and reposts per post 3. **`get_follower_growth`** — check the growth trend over the last 30 days 4. **`get_recommendations`** — retrieve platform-generated suggestions from BlackTwist Do not present raw numbers. Interpret them directly into the recommendation framework below. ### Path C — No BlackTwist If BlackTwist is unavailable and no prior analysis exists, ask the user to share what they know: > "To give you the most useful recommendations, I need a quick picture of what's working. Can you share: > - Your 2–3 best-performing posts (what you posted, approximate engagement) > - Your 2–3 worst-performing posts > - Your current posting frequency > - Your primary goal right now (growth, engagement, conversions, other) > > Even rough answers unlock much better recommendations than starting blind." Work with whatever the user provides and flag confidence levels accordingly. --- ## Recommendation Framework Organize every recommendation into one of four tiers, ordered by implementation effort. Present them in this order — quick wins first. ### Tier 1 — Quick Wins **Changes under one hour that are likely to improve results immediately.** These are execution adjustments, not strategic overhauls. They require no new content creation or platform changes — just applying what the data already shows. Examples: - "Start every post with a specific number — your top 3 posts all open with a stat and average 3× your baseline engagement rate" - "Shift your Friday posts to Wednesday — Friday averages 1.8% ER vs. 5.1% on Wednesday" - "Add 'Save this for later' to the end of your educational posts — your how-to content gets high impressions but 60% fewer saves than your average" Each quick win must cite a specific data point, not a general principle. **Example quick win:** ``` Quick Win #1: Start every educational post with a specific number Why: Your top 3 posts all open with a stat (avg 7.8% ER vs. 3.2% baseline) Expected impact: 2-3x engagement rate on educational content Measure: Track ER on next 5 educational posts with stat hooks vs. previous 5 without ``` ### Tier 2 — Strategic Shifts **Bigger changes to content mix, platform focus, or cadence that require 2–4 weeks to implement and measure.** These are the recommendations that compound over time. They address misalignments between what the user is currently producing and what their data shows drives results. Examples: - "Shift 20% of your motivational content to storytelling — your personal story posts outperform motivational posts by 40% on engagement rate and drive 3× more comments" - "Reduce LinkedIn posting from daily to 4× per week and invest the saved time into longer-form threads — your engagement rate drops on days when you post twice, suggesting q
Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.
Install
Pinned to the audited commit c480812
git clone https://github.com/blacktwist/social-media-skills git -C social-media-skills checkout c4808127928a
The author documents no install command, so this uses the repository directly. Our verdict covers commit c4808127928a only.
Works in
The author has not said which agents this skill supports, and we have not tested it in any.
Audit history
Every audit, every source change
- ✓SAFE B 89 / 100
first audit · source
c4808127928a
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Questions about Optimization Advisor Sms
What does the Optimization Advisor Sms skill do?
Is Optimization Advisor Sms safe to install?
What can Optimization Advisor Sms access on my machine?
How current is this page?
Sources
- github.com/blacktwist/social-media-skills/tree/main/skills/optim — the audited source at commit c4808127928a and every finding aboveObserved · 19 Oct 2026
Spotted something wrong? Report a correction · Methodology
Keep going in your AI
Opens with this page as the source. We add nothing else to the prompt.
- What does the Optimization Advisor Sms skill do?
- Is Optimization Advisor Sms safe to install?
- What can Optimization Advisor Sms access on my machine?