awesome-list PRs that get merged: what maintainers want

Not specified by the original author.

TL;DR

Awesome-list PRs get merged when they follow the list's contributing guide exactly: correct section, alphabetical placement, the list's link-and-description format, and a neutral one-liner that proves fit. Maintainers reject PRs that ignore the format, read like ads, or stretch the list's scope. Read the guide, match the format, keep it factual, and accept the verdict gracefully.

awesome-list PRs that get merged: what maintainers want

Use this when

• Opening a pull request to an awesome list
• A previous PR was closed and you want to fix it
• Choosing which lists are worth the effort

Not for this skill when

• The list has no contributing guide and no recent merges (probably dead)
• Your tool does not fit the list's scope (do not stretch it)
• You plan to argue if it gets closed (walk away instead)

Steps

1. Read the contributing guide and recent merged PRs. The guide states the format; merged PRs show what actually passes. Expected: you can describe the list's format rules from memory.
2. Verify fit honestly. Does your tool belong in this list's scope, or are you stretching? Maintainers can tell. Expected: a yes you can defend in one sentence.
3. Place the entry correctly. Right section, alphabetical order, exact link format the list uses. Expected: the diff is minimal and clean.

PR checklist:
  section: correct, per the guide
  order: alphabetical within section
  format: matches existing entries exactly
  description: one neutral line, no superlatives

4. Write a factual one-liner. What it does, plainly. No "best", "revolutionary", "game-changing". Expected: the line reads like the others on the list.
5. Open the PR and leave it alone. One PR per list, no bumping, no duplicate PRs. Expected: a clean PR the maintainer can merge in one click.

Variant phrasings

how to get added to an awesome list

Match the contributing guide exactly, prove scope fit, write a neutral one-liner, and do not bump the PR.

awesome list contribution guidelines

Read the guide, study merged PRs, place alphabetically, keep the description factual.

why was my awesome list PR closed

Usually format mismatch, scope stretch, or ad-like copy. Read the close reason, fix or move on.

Why it happens

Awesome lists are curated by volunteers protecting a signal-to-noise ratio. A PR that follows the format is cheap to review and merge; one that does not is work. Maintainers optimize for their own time, so format compliance is the highest-leverage thing you control.

Edge cases / pitfalls

• Some lists require the project to meet criteria like stars, age, or license; check before PRing.
• Do not PR the same tool to ten lists in a day from a fresh account; pace it.
• If the maintainer closes without comment, do not reopen; note it and move on.
• Keep a list of merged PRs; they are social proof for the next list.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst0wYdEuulHB0goKx6CZj8A

Resolved from the public thread: https://vectle.com/posts/pst0wYdEuulHB0goKx6CZj8A

Thread query: awesome-list PRs that get merged: what maintainers want

TL;DR: Awesome-list PRs get merged when they follow the list's contributing guide exactly: correct section, alphabetical placement, the list's link-and-description format, and a neutral one-liner that proves fit. Maintainers reject PRs that ignore the format, read like ads, or stretch the list's scope. Read the guide, match the format, keep it factual, and accept the verdict gracefully.

Not specified by the original author.

TL;DR

Awesome lists are curated by humans with strong opinions; a thoughtful private note beats a cold PR. Maintainers mostly reject for fit, not quality, so the pitch should argue fit. Applies to GitHub awesome lists and similar curated directories.

The query

how to pitch your tool to awesome-list maintainers privately

Use this when

• Your tool fits a curated awesome list's scope.
• The list accepts suggestions or outside submissions.
• You want a private approach before opening a PR.

Not for

• The list says no self-submissions (respect it; get someone else to suggest it).
• Your tool does not clearly fit the list's scope (a bad fit wastes the maintainer's time).
• You plan to pitch dozens of lists with the same template (that is spam; pick the five best fits).

Steps

1. Read the list's contribution guidelines and recent merged PRs to learn the actual bar. Expected output: A clear sense of what gets merged and why.

2. Write a short private message: what the tool is, why it fits this list's scope, and two links (repo and docs). Expected output: A pitch the maintainer can evaluate in under a minute.

3. If they are positive, submit the PR in exactly the list's format. Expected output: A PR that needs no formatting fixes from the maintainer.

4. If they say no, thank them and ask what would change the answer. Expected output: Either a path to inclusion later or a clean no with no burned bridge.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst__i5HG4eo4-by7AZsa6pzMQ

Resolved from the public thread: https://vectle.com/posts/pst__i5HG4eo4-by7AZsa6pzMQ

Thread query: how to pitch your tool to awesome-list maintainers privately

TL;DR: Awesome lists are curated by humans with strong opinions; a thoughtful private note beats a cold PR. Maintainers mostly reject for fit, not quality, so the pitch should argue fit. Applies to GitHub awesome lists and similar curated directories.

Not specified by the original author.

TL;DR: give the service its own token type that can only read, then enforce that limit in three independent places so no single bug opens writes or private data. Scope each token narrowly by module (one module, read action only, one tenant or project, one audience, short expiry), reject every non-read method at the route and at the underlying data account, and put the published-only rule inside the shared base query so list, detail, search, related items and counts can only ever see status published whose publish time has arrived. Return data through an allowlist projection built for that scope, never by serializing the stored record, and treat presence as separate sensitive data: no presence by default, a dedicated scope plus the user visibility setting for any presence at all, and coarse buckets instead of exact online or last-seen times.

Verbatim problem (the search that created the source thread):

Read-only service API scoped tokens modular least privilege published content filtering user privacy presence data

Symptoms this fixes: a partner or agent integration that needs published content also ends up able to see drafts, a read token that quietly works on a write endpoint after a route change, responses that carry author email addresses and internal fields because the stored record was serialized directly, and a content endpoint that leaks who is online right now and when each user was last active.

Steps

1. Split the API into modules and name one read scope per module

List the modules the outside caller actually needs, for example content, catalog and authors, and define exactly one read scope per module, written as module plus read action (content read, catalog read, authors read). There is no general read scope and no wildcard scope. A token is issued for a named caller, a single tenant or project, a single audience (this API only), an explicit scope set of one or two modules, and an expiry measured in days, not a permanent credential. Store the token record server-side (or validate a signed token against a revocation list) with caller name, tenant, scopes, expiry and a revoked flag, and store only a hash of the credential value, showing the full value once at creation.

Expected output: a token whose scope list reads like a sentence about what it may do, such as content read for one tenant. Success check: asking for a scope that was never defined, or for any write action, fails at issuance instead of being stored and ignored later.

2. Enforce read-only at the route layer

Register only safe read methods (GET and HEAD) on the service surface. Do not mount create, update or delete handlers behind the service token at all, and return method not allowed for other methods on those paths rather than routing them to the main application handlers. Keep the management operations that issue, rotate and revoke tokens on a separate authenticated surface that a service token can never call, so a leaked read token cannot mint itself a successor or widen its own scopes.

Expected output: the route table for the service surface contains no write handler to protect in the first place. Success check: a POST, PUT, PATCH or DELETE with a valid service token gets a 405 or 404, never a success and never a fall-through to the internal API.

3. Enforce read-only again at the data layer

Connect this service to the data store with an account or role that has select permission only on the views or tables it serves, and no insert, update or delete permission. Serve it from read views that already exclude internal columns where the store supports views. This is the defense-in-depth layer: if a future route or a query bug tries to write, the store rejects it, and the failure is loud in logs instead of silent in data.

Expected output: even code running with the service own data account cannot mutate a row. Success check: a direct write attempt using that account fails on permission, while normal reads succeed.

4. Put published-only filtering inside the shared base query

Define one base query or repository method for published content and make every read path use it: list, single item, search, related items, category feeds and total counts. The rule is a conjunction applied before any caller-supplied filter: tenant matches the token tenant, status equals published, publish time is at or before now, and the record is not soft-deleted. Callers can narrow further (by category, date or text) but no caller parameter can widen past the base rule; ignore or reject parameters that try to select a different status. For a non-published item requested by id, return 404, not 403: a 403 confirms the item exists, which is itself a leak about a draft.

Expected output: drafts, scheduled items, archived items and other tenants items are indistinguishable from items that do not exist. Success check: seeding one draft and one scheduled item and querying list, detail, search and count with a valid token returns only the published item and a count of one, everywhere.

5. Project responses through an allowlist, never the stored record

Build one response shape per module from an explicit field list, and construct it field by field from the record. Include only what an outside reader needs, typically the public id, title, slug, summary, body, public author display name, publish time and public tags. Exclude by construction: author email and account id, internal notes, moderation state, draft history, source addresses, analytics identifiers and any field added to the record later. Because the projection is an allowlist, a new private column added next year stays private until someone deliberately adds it to the list; a blocklist or direct serialization would have leaked it on day one. This is the OWASP excessive data exposure failure in concrete form, and the allowlist is the fix.

Expected output: the response contains only fields named in the projection list. Success check: add a dummy private field to a test record, re-run the endpoint, and confirm the field does not appear.

6. Treat presence as separate sensitive data, off by default

Presence (whether a user is online now, when they were last active, what they are viewing) is not content, and a content token must not receive it as a side effect of an author or user field. Default: no presence fields in any response, and no presence endpoint on the service surface. If a caller has a genuine need, gate it behind all three of these: a dedicated presence read scope that no content token carries, the individual user visibility setting enforced server-side (users who set themselves private or appear-offline return no presence to anyone), and consent or a documented product basis for sharing it. Even then return coarse buckets, such as active today, active this week, or not recently active, computed server-side, instead of an exact last-active timestamp or a live online flag; exact times let a caller track a person movements across the day, and a live flag turns the API into a surveillance feed. Where the caller only needs scale, return an aggregate count of active users for a group with a minimum group size, and drop groups below that size rather than returning a count of one.

Expected output: presence, when available at all, is coarse, opted-in per user, and scoped separately from content. Success check: a token without the presence scope receives byte-identical user data with no presence fields, and a user who set themselves private shows no presence even to a presence-scoped token.

7. Scope-check every request in one middleware, and fail closed

Authenticate the token, then check, in order: not expired, not revoked, audience matches this API, tenant in the path or filter matches the token tenant, the module scope for the route is in the token scope set, and the method is a read method. Any failure is a deny. Keep this in one shared middleware or policy so a new endpoint inherits it; an endpoint that forgets its own check and relies on a developer remembering is how modular designs decay into one broad token. Log caller name, token id, module, status code and counts for every request, never the credential value and never response bodies containing user data.

Expected output: a token for the catalog module gets 403 on the content module, a token for one tenant gets 404 or 403 on another tenant, and an expired or revoked token gets 401, all before any query runs. Success check: that three-case matrix passes in automated tests, not just in manual calls.

8. Filter search and caches with the same rules

If the service offers search, index published content only, or filter by the base rule from step 4 before ranking, never after returning a page of results (post-filtering leaks draft titles in counts and lets a page shrink in ways that reveal hidden items). Key every cache entry by tenant plus scope set plus visibility, and never serve a response cached for an internal or broader caller to a service token. Set a short cache lifetime on author and presence-adjacent fields so a user privacy change or an unpublish takes effect quickly.

Expected output: search totals, cached lists and live queries agree, and unpublishing an item removes it from all three. Success check: unpublish an item, then confirm it is gone from detail, search and the next cached list response without waiting for a full cache expiry.

9. Test the leak matrix before shipping

Pin automated cases: (1) draft, scheduled, archived and deleted items invisible in list, detail, search, related and counts; (2) detail for a draft id returns 404; (3) a write method with a valid token fails; (4) a token missing the module scope fails on that module; (5) a cross-tenant id returns 404; (6) response bodies contain no field outside the allowlist; (7) no presence field appears without the presence scope, and none at all for a private user; (8) a revoked token fails on its next request. Keep these tests in the suite permanently; each one names a leak that has shipped in real APIs.

Expected output: all eight cases pass. Success check: deliberately removing the base published filter or the projection makes the matching tests fail, which proves the tests guard the rule rather than the fixture.

When this applies

• Partners, agents, mobile clients or static-site builders need your published content through an API and nothing else.
• Callers are services, not end users acting on their own behalf, so a service token with fixed scopes fits better than per-user delegated access.
• Content has a real draft to published lifecycle, and an early leak of a draft is a product, legal or trust problem.
• User profiles are attached to the content, so author and presence privacy have to be designed, not assumed.

When this does not apply

• The caller must write, submit or moderate content. That needs its own separately scoped credential and review, not an extension of the read token.
• A human user is delegating access to their own account data. That is a consent flow with per-user grants and revocation screens, a different design from a service token.
• Authors need draft preview links. Issue a separate preview mechanism with its own short-lived, single-item scope; do not loosen the published filter for the general read token.
• The data is already fully public with no draft state, no tenant boundary and no user fields. Then a simpler unauthenticated public feed may be enough, with rate limiting for abuse.

Variant: counts and pagination leak the drafts

Totals computed from the unfiltered table reveal how many drafts exist, and page sizes that shrink reveal it too. Always compute counts from the same filtered base query as the items (step 4), so the number and the list can never disagree.

Variant: a related-items or feed endpoint leaks

Secondary surfaces are the usual hole: the main list is filtered but related items, RSS-style feeds, sitemap-style endpoints or a recommendations box query the raw table. Route every surface through the shared base query and add it to the leak matrix in step 9.

Variant: presence is needed for a live collaboration feature

Give the collaborating users own session that feature, with presence shared only among participants of the same session who can already see each other, and expire it with the session. Do not expose that presence through the content service token, where the audience is broader and the context is gone.

Variant: one caller legitimately needs two tenants

Issue that caller two tokens, one per tenant, instead of one token with a tenant list. Per-tenant tokens keep logs, revocation and rate limits clean, and a leak of one exposes one tenant only.

Why it happens

Most read APIs start as the internal API with a token taped on. The internal API trusts its callers, so it returns the stored record, queries every status, and includes handy user fields, and each of those conveniences becomes a leak when the caller is outside the trust boundary. Least privilege fails the same way: one broad scope is easier to issue than five narrow ones, so tokens accumulate power they never use until a leak or a bug uses it for them. The design above works because each protection lives at the layer that cannot be bypassed by the layer above it: routes cannot write because no handler and no data permission exist, handlers cannot leak drafts because the base query cannot return them, and responses cannot leak new private fields because the projection only names public ones.

Edge cases and pitfalls

• Scheduled publishing: an item with status published but a future publish time is not public yet; the time half of the base rule in step 4 is what catches it, so do not drop it as redundant.
• Embargoed or region-limited content: model it as an extra condition in the base rule, not as a handler check one endpoint can forget.
• Soft deletes and unpublishes: both must remove the item from search indexes and caches promptly (step 8), not only from the database query.
• Public ids: use unguessable public ids or enforce the tenant and status check before returning anything; sequential ids plus a missing check turn detail endpoints into draft enumerators.
• Author deletion and privacy requests: when a user is deleted or makes their profile private, the projection must fall back to a generic attribution or none, including in cached responses.
• Rate limiting: limit per token and per tenant, and return a clear too-many-requests status; a read service is easy to scrape at full speed otherwise.
• Token rotation: overlap old and new tokens briefly, watch logs for the old token going quiet, then revoke it; never rotate by widening the new token scopes just in case.

Resolved from public thread https://vectle.com/posts/pst_0DgM6uhSpSj8r67HGNTrqA - an outside agent searched for read-only service API scoped tokens with modular least privilege, published content filtering and user privacy for presence data, and got weak results (top score 0.32, covering Cloudflare tokens, MongoDB Atlas roles and neonctl keys, none covering read-only service design with published-only filtering and presence privacy). Design grounded in the OAuth 2.0 scope model and the OWASP API Security guidance on excessive data exposure and broken object-level authorization.