mcpbeat

New Lint

supabase/new-lint

Create a new splinter lint — a SQL view that checks for a database anti-pattern. Use this skill when the user asks to add a lint, create a new check, implement a linting rule, or extend splinter with a new detection.

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on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/supabase/splinter --skill new-lint

The instruction itself

13 sections, as written by the author

Create a New Splinter Lint

You are implementing a new lint for the splinter PostgreSQL linting tool. Follow every step in order. Do not skip steps.

Step 1 — Determine the next lint number

Glob lints/*.sql and find the highest numeric prefix. Increment by 1 to get the new lint ID (zero-padded to 4 digits, e.g. 0025). Use this as XXXX throughout.

The lint's machine name (the name column) is derived from the argument: lowercase, underscores, no leading digits.

Step 2 — Create lints/XXXX_<name>.sql

Create a SQL view in the lint schema. The view must return exactly these 10 columns in this order:

| Column | Type | Notes |

|--------|------|-------|

| name | text | snake_case identifier, e.g. 'my_lint_name' |

| title | text | Human-readable title |

| level | text | 'ERROR', 'WARN', or 'INFO' |

| facing | text | 'EXTERNAL' or 'INTERNAL' |

| categories | text[] | e.g. array['SECURITY'] or array['PERFORMANCE'] |

| description | text | What the lint checks and why it matters |

| detail | text | format()-interpolated message naming the specific object |

| remediation | text | 'https://supabase.com/docs/guides/database/database-linter?lint=XXXX_<name>' |

| metadata | jsonb | jsonb_build_object('schema', ..., 'name', ..., 'type', ...) |

| cache_key | text | format('<name>_%s_%s', schema, object) — unique per violation |

Copy guidance for Advisor surfaces:

  • Keep description to 1-2 short sentences: what the lint detects and the first likely action.
  • Keep detail concise and object-specific. It should describe the failing object, not restate the full rationale.
  • Put deeper explanation, edge cases, and extended remediation in docs/XXXX_<name>.md, not in the SQL strings.

Required conventions:

  • Always prefix all catalog references: pg_catalog.pg_class, pg_catalog.pg_namespace, etc.
  • Always exclude system schemas using this exact list:
  nsp.nspname not in (
      '_timescaledb_cache', '_timescaledb_catalog', '_timescaledb_config',
      '_timescaledb_internal', 'auth', 'cron', 'extensions', 'graphql',
      'graphql_public', 'information_schema', 'net', 'pgmq', 'pgroonga',
      'pgsodium', 'pgsodium_masks', 'pgtle', 'pgbouncer', 'pg_catalog',
      'pgtle', 'realtime', 'repack', 'storage', 'supabase_functions',
      'supabase_migrations', 'tiger', 'topology', 'vault'
  )
  • End with a deterministic ORDER BY (e.g. ORDER BY schema_name, table_name) — required for stable pg_regress output
  • Never select raw OIDs, ctids, timestamps, or sequences in output columns — they vary between runs
  • If using array_agg, always specify ORDER BY inside the aggregate for deterministic element order
  • Use CTEs for complex logic

Data API exposure filters (REQUIRED when the lint flags risks from Data API surface area):

If the lint is about a risk that only matters when a database object is exposed via a Supabase Data API (PostgREST and/or pg_graphql) — e.g. "X is accessible to anon/authenticated", "Y leaks via the API", "Z is reachable from clients" — you must filter to schemas that are actually exposed. Without this filter, the lint will false-positive on objects that exist in non-exposed schemas.

  • PostgREST and pg_graphql both read their exposed schemas from pgrst.db_schemas (a comma-separated GUC). Always add this predicate so the lint only fires when the object's schema is in that list:
  and <schema_column> = any(array(select trim(unnest(string_to_array(current_setting('pgrst.db_schemas', 't'), ',')))))

The 't' (missing_ok) argument is important — it prevents an error when the setting is unset. See lints/0023_sensitive_columns_exposed.sql and lints/0016_materialized_view_in_api.sql for working examples.

  • If the risk is GraphQL-specific (i.e. it would not exist if only PostgREST were enabled — for example, a problem that surfaces through the generated GraphQL schema), additionally require that the pg_graphql extension is installed:
  and exists (select 1 from pg_catalog.pg_extension where extname = 'pg_graphql')

See lints/0014_extension_in_public.sql for the pg_catalog.pg_extension query pattern.

  • If the lint is purely a "table best practices" check (e.g. missing primary key, unindexed FK, duplicate index) that applies regardless of API exposure, do not add these filters — they would mask legitimate findings on internal-only schemas.
  • Tests for lints with these filters must set local pgrst.db_schemas = 'public'; inside the test transaction (see the test template in Step 5). For GraphQL-gated lints, the test also needs create extension if not exists pg_graphql; (and a corresponding teardown) so the positive case can fire.

Template:

create view lint."XXXX_<name>" as
select
    '<name>' as name,
    '<Title>' as title,
    'WARN' as level,
    'EXTERNAL' as facing,
    array['SECURITY'] as categories,
    '<Description of what is checked>' as description,
    format(
        '<detail message with `%s`.`%s` references>',
        schema_name,
        table_name
    ) as detail,
    'https://supabase.com/docs/guides/database/database-linter?lint=XXXX_<name>' as remediation,
    jsonb_build_object(
        'schema', schema_name,
        'name', table_name,
        'type', 'table'
    ) as metadata,
    format('<name>_%s_%s', schema_name, table_name) as cache_key
from
    -- your query here
order by
    schema_name,
    table_name;

Step 3 — Update bin/installcheck

Read bin/installcheck. Find line 55 — the long psql command that loads all lint files. It currently ends with something like:

-f lints/0024*.sql -d contrib_regression

Insert the new lint before -d contrib_regression, maintaining numeric order:

-f lints/0024*.sql -f lints/XXXX*.sql -d contrib_regression

Step 4 — Create docs/XXXX_<name>.md

**Level:** WARN|ERROR|INFO

**Summary:** One-line summary of what is detected.

**Ramification:** What goes wrong in production if this is ignored.

---

### Rationale

Why this pattern is problematic. Include context about the Supabase platform where relevant.

### How to Resolve

**Option 1: [Preferred fix]**

-- Example SQL showing the fix


**Option 2: [Alternative]**

-- Alternative fix


### Example

Given this problematic configuration:

-- The bad pattern


Fix:

-- The corrected version


### False Positives

Cases where this lint may fire when the pattern is intentional, and how to handle them.

Step 5 — Create test/sql/XXXX_<name>.sql

Structure the test file exactly as follows:

begin;
  set local search_path = '';
  -- Add the following line only if your lint uses pgrst.db_schemas:
  -- set local pgrst.db_schemas = 'public';

  -- BASELINE: 0 issues on empty schema
  select * from lint."XXXX_<name>";

  savepoint a;

  -- NEGATIVE EXAMPLE: a similar-looking pattern that should NOT trigger
  -- Explain why this should not fire (comment required)
  -- ... DDL ...
  select * from lint."XXXX_<name>";  -- expect 0 rows

  rollback to savepoint a;

  -- POSITIVE EXAMPLE: the problematic pattern that SHOULD trigger
  -- Explain what makes this a violation (comment required)
  -- ... DDL ...
  select name, detail, cache_key from lint."XXXX_<name>";  -- expect 1+ rows

  -- RESOLUTION: apply one of the documented fixes
  -- ... DDL fix ...
  select * from lint."XXXX_<name>";  -- expect 0 rows

rollback;

Stability rules — pg_regress does exact string comparison across every run:

  • Use fixed, explicit object names (never random/generated)
  • Project only the columns needed to verify correctness — avoid select * for wide/variable output
  • Prefer projecting name, detail, cache_key for positive cases rather than select *
  • Never rely on row order that isn't guaranteed by the lint's ORDER BY
  • Never reference OIDs, system-generated values, or version-specific catalog details
  • Never use count(*) when a projected select of 0/1 rows is more informative and equally stable

Step 6 — Run Docker tests and generate test/expected/XXXX_<name>.out

Always use Docker — local Postgres versions may produce subtly different output:

docker rmi -f dockerfiles-test && SUPABASE_VERSION=15.1.1.13 docker-compose -f dockerfiles/docker-compose.yml run --rm test

Results are written to results/ (mounted volume). Read and verify results/XXXX_<name>.out before promoting:

  • Baseline query → (0 rows)
  • Negative example → (0 rows)
  • Positive example → expected row(s) with correct name, detail, cache_key values ✓
  • Resolution example → (0 rows)
  • No SQL errors anywhere in the file ✓

Only after verification:

cp results/XXXX_<name>.out test/expected/XXXX_<name>.out

Step 7 — Update test/sql/queries_are_unionable.sql

Read the file. Before the final semicolon (on the last select * from lint."0024_..." line), append:

    union all
    select * from lint."XXXX_<name>"

The file ends with a semicolon after the last view reference, then rollback;. Add the new entry before that semicolon.

Step 8 — Verify and promote test/expected/queries_are_unionable.out

The Docker run from Step 6 already produced results/queries_are_unionable.out. Read and verify it:

  • The SQL echo must include the new union all select * from lint."XXXX_<name>" line ✓
  • The result must be (0 rows)
  • No SQL errors ✓

Only after verification:

cp results/queries_are_unionable.out test/expected/queries_are_unionable.out

Step 9 — Regenerate splinter.sql

python bin/compile.py

This rebuilds splinter.sql as a UNION ALL of all lint views. Verify the new lint appears in the output file.

Step 10 — Install pre-commit hooks (if not already installed)

pre-commit install

This ensures bin/compile.py runs automatically on every commit to keep splinter.sql in sync.


Verification Checklist

Run the full Docker suite one final time:

docker rmi -f dockerfiles-test && SUPABASE_VERSION=15.1.1.13 docker-compose -f dockerfiles/docker-compose.yml run --rm test

Then check:

  • [ ] results/regression.diffs is empty (no unexpected diffs)
  • [ ] git diff test/expected/ shows only the new files you intentionally added/changed
  • [ ] splinter.sql includes the new lint in the UNION ALL
  • [ ] lints/XXXX_<name>.sql exists
  • [ ] docs/XXXX_<name>.md exists
  • [ ] test/sql/XXXX_<name>.sql exists
  • [ ] test/expected/XXXX_<name>.out exists

Key Reference Files

| What to copy | From |

|---|---|

| System-schema exclusion list | lints/0024_rls_policy_always_true.sql lines 38–40 |

| Extension-owned object filter (pg_depend) | lints/0001_unindexed_foreign_keys.sql |

| pgrst.db_schemas API exposure check | lints/0023_sensitive_columns_exposed.sql, lints/0016_materialized_view_in_api.sql |

| pg_graphql extension-enabled check | lints/0014_extension_in_public.sql (for the pg_catalog.pg_extension pattern) |

| begin/savepoint/rollback test structure | test/sql/0024_rls_policy_always_true.sql |

| Doc format | docs/0024_permissive_rls_policy.md |

How to use it

Copy the folder

Take supabase/new-lint from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference docker. Without those the skill loads but fails at the first command.