trend-mastodon

name	trend-mastodon
title	Mastodon Trend Harvester Playbook
description	Platform-specific intel for harvesting Mastodon trends across federation — boost-driven amplification, per-instance culture map, hashtag-following discovery, harvest URLs across home + niche instances, content-warning conventions, alt-text expectations, and dead patterns in 2026. Activates inside an octoweb:trend session whenever the user names Mastodon.
license	Apache-2.0
compatibility	Octoweb browser access. Signed-in session on the user's home instance recommended for federated timeline; logged-out works for instance trends pages and hashtag pages.
capabilities	octoweb memory-read memory-write
domains	octoweb
rules	["session(trend) content(mastodon)","session(trend) content(fediverse)","match(\\b(mastodon|fediverse|fedi)\\s+(trend|trends|harvest|brief|post|toot)\\b)","match(\\b(harvest|scan|analyze)\\s+(mastodon|fediverse)\\b)"]

Overview

This skill carries the platform-specific mechanics the octoweb:trend agent needs to harvest Mastodon — current federation ranking signals, per-instance harvest URLs, scoring on boost paths, hashtag-following targeting, content-warning conventions, alt-text expectations, dead patterns, timing. The agent owns the shared DNA loop; this skill plugs the Mastodon parameters in.

Mental model

Mastodon has no global feed and no algorithmic ranker — reach happens through boosts (its term for reposts) and through the hashtag-following feature. Each instance has its own local culture, content-moderation rules, and trends page. What you see depends on which instance you queried. Federation is slow — give posts 48–72h to develop boost chains. Marketing voice is detected and muted within seconds on tech instances. Image alt-text is expected — posts with images lacking alt-text get scolded and lose boost potential on dev/tech instances. Calibrate per instance.

Rules

Current ranking and amplification signals (2026)

Signal	Effect
Boosts	Primary amplification mechanism (no algorithmic feed)
Boost-to-favourite ratio	>0.20 strong federation, >0.40 breaking through to other instances
Hashtag follows	Underused growth lever — users follow hashtags directly
Cross-instance reach	Same post appearing in 3+ instance trends pages = federation-viral
Image alt-text quality	Expected; lacking alt-text loses boost potential on dev/tech instances
External links in root	NOT suppressed — Mastodon treats links normally
Content warnings (CWs)	Required by culture on politics / NSFW / long-thread / hot-take; not on ordinary tech posts
Cross-post-from-X residue	Detected and muted

Harvest surfaces (run in parallel)

For the user's home instance:

Surface	URL	Yields
Home trends	https://<home-instance>/explore	What the home instance's algorithm-light surface pushes
Home local	https://<home-instance>/public/local	Posts originating on the home instance (culture signal)
Federated timeline	https://<home-instance>/public	All federated posts the instance has seen
Home hashtag	https://<home-instance>/tags/<tag>	Federation-aware topic feed

For 2–4 niche-relevant instances (for AI / agents / LLM / RAG / Codex / startup niche, common candidates include hachyderm.io for devs, fosstodon.org for FOSS, mastodon.social for general, tech.lgbt, mas.to):

Surface	URL	Yields
Niche-instance trends	https://<niche-instance>/explore	Where dev/tech trends actually surface
Niche-instance local	https://<niche-instance>/public/local	Local culture of that instance
Niche-instance hashtag	https://<niche-instance>/tags/<tag>	Hashtag followers on tech-heavy instances

Anchor profiles:

• https://<instance>/@<handle> — last 7 days per anchor

Run 5–8 in parallel. Mastodon paginates traditionally — usually one snapshot per tab surfaces enough posts.

Scoring rubric (Mastodon-specific signals)

Virality axis 0–5:

• Boost-to-favourite ratio — primary federation signal
• Absolute boost count (>20 boosts in 48h on a <5k account = climbing the federation graph)
• Reply-thread depth — top-level replies that get replies
• Cross-instance reach — same post in 3+ instance trends pages = federation-viral
• Hashtag-follow surfacing — posts on hashtags with many followers reach more eyes; verify hashtag size at runtime

Niche-fit axis 0–5 — universal scale.

Do not score on view counts — Mastodon doesn't surface them.

Hook taxonomy currently winning

1. Honest technical observation
2. Earnest question with specific context
3. First-person story with technical detail
4. Careful contrarian — backed by experience, not vibes
5. Receipt — image / chart / screenshot + 1–2 lines + thoughtful alt-text
6. Reasoned recommendation between two tools / approaches
7. Thoughtful pull-quote with brief commentary (a quote toot)

Dead patterns

• "Follow for more!" / X-style growth-hack closing
• Hashtag stacks (>3 hashtags reads as spam faster than on X)
• Cross-post tells from X ("RT @...", "via Twitter")
• Marketing voice
• Images without alt-text
• "Birdsite" complaining (dead pattern as of 2024+)
• AI vocabulary in hook line
• Skipped CW on a politically charged or NSFW post

Format and length

Goal	Length (default cap 500)	Format
Quick take	100–300 chars	Single
Thread	3–6 self-replies, each substantive	Native — depth over chain length
Image post	300–500 chars + 1–4 images with alt-text	Strong default
Long post	1000–5000 chars on instances with raised caps	Sparingly — CW it

Hashtag prescription

For each recommended post, prescribe 1–3 hashtags:

• One niche-specific (e.g. #LLM #RAG #AIAgents #Rust #FediVerse)
• Optionally one community-cultural (e.g. #TechHire, #100DaysOfX)
• Optionally one timing-tied tag for live events

Verify hashtag size at runtime via /tags/<tag> — empty hashtag pages are dead tags. Recommend only tags with active recent posts.

Content warning (CW) conventions

• Politics / NSFW / hot-take / very-long-thread → CW required
• Ordinary technical posts → no CW
• Skipped CW on politically charged content = quiet hide by reader defaults
• Misused CW on ordinary tech content = looks performative, kills boost potential

Anchor accounts

Identify 5–10 niche-relevant accounts whose boost would amplify the user's post. Note follower band, instance, and recent boost behavior. Cross-instance anchors (e.g. a hachyderm.io anchor for a fosstodon post) drive federation reach faster than same-instance anchors.

Timing

• Best windows (mixed timezone): Tue–Thu 8 AM–12 PM ET (catches Europe afternoon + US morning); second wind 4–7 PM ET
• Federation is slow — give posts 48–72h to develop
• Weekend mornings work for personal / technical writing

Saturated-take detection

Mastodon's tech-niche saturated takes in 2026 cluster around: "ActivityPub vs AT-Proto," generic "Why I left X" posts (still common 3 years in), "FOSS ethics" debates, repeated "AI is theft" / "AI is fine" cycles. Verify saturation live.

Examples

Example 1: Full DNA + boost-path call

Bad — count without federation context:

@dev got 40 boosts on a post about RAG.

Good — federated handle, boost-path, alt-text quality noted:

@[e-mail] (3.8k followers) — 92⭐ / 47🔁 / 18💬
Boost-to-favourite ratio: 0.51 — federation breakout
Boost path: originated on hachyderm.io → boosted into fosstodon.org local trends within 6h → cross-surface in 2 other instance trends pages by 24h
Anchor @[e-mail] boosted at 5h mark, drove second-instance amplification
> Spent two weeks reading the actual RAG papers everyone cites. Three out of five contradict the benchmark methodology people quote them for.
Hook type: receipt-promise + named contrarian observation
Length: 217 chars
Format: single post + image (chart) with 3-line alt-text explaining the methodology gap
Hashtags: #LLM #RAG (2 — within limit, both with active follower coverage)
No CW (correctly — pure technical content)
DNA: technical-tone + first-person artifact + cross-instance anchor amplification

Example 2: Alt-text rejection

@handle@instance — 200⭐ / 8🔁 (boost ratio 0.04, far below 0.20 floor)
Image attached: chart, no alt-text
Replies: 3 of 18 are alt-text scolds asking for description
Lesson: alt-text-less image posts get scolded into low boost-ratio. Always prescribe alt-text quality on image-attached recommendations.

Checklist

Before returning the Mastodon section of the brief:

• Home instance + 2–4 niche-relevant instances queried
• Every cited post has full federated handle (@[e-mail]), boost count, favourite count, reply count, URL, CW state
• Boost-to-favourite ratio computed and used as primary signal
• Boost path noted on every cited example (origin instance → instances it spread to)
• No score depends on view counts
• (Opt-in mode only) Hashtag prescriptions verified at runtime via /tags/<tag> — no dead tags
• (Opt-in mode only) CW prescribed for politics / NSFW / hot-take / long-thread; explicitly NOT for ordinary tech posts
• (Opt-in mode only) Alt-text quality requirement included for any image-attached recommendation
• Anchor-account boost-path list (5–10 accounts, instance noted, follower band) — research output: shows who currently amplifies, not who to target
• Dead-pattern list applied — no recommendation uses X-residue, hashtag stacks (>3), marketing voice, or skipped-CW patterns
• (Opt-in mode only) Instance-targeting plan included (primary home instance + 2–3 niche instances to escape into)
• All background tabs closed

Composition / References

• Pairs with social-mastodon (content domain) for writing the actual post from the brief.
• Mastodon handles include the instance: always cite @[e-mail] — never bare @user.
• Use the agent's universal output schema.