Release
hypequery/hypequery
Cut a stable hypequery release via Changesets, or explain/check the canary flow.
A skill your agent uses to migrate identified PostgreSQL tables to Timescale/TimescaleDB hypertables with optimal configuration and validation.
The automated check flagged lines worth reading first. See the safety section below.
$ npx skills add timescale/pg-aiguide --skill migrate-postgres-tables-to-hypertables -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install timescale/pg-aiguide migrate-postgres-tables-to-hypertables --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/timescale/pg-aiguide.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/migrate-postgres-tables-to-hypertables .claude/skills/migrate-postgres-tables-to-hypertables && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "migrate-postgres-tables-to-hypertables" agent skill from https://github.com/timescale/pg-aiguide/tree/main/skills/migrate-postgres-tables-to-hypertables into .claude/skills/migrate-postgres-tables-to-hypertables/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "migrate-postgres-tables-to-hypertables", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/timescale/pg-aiguide/tree/main/skills/migrate-postgres-tables-to-hypertablesType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add timescale/pg-aiguide --skill migrate-postgres-tables-to-hypertables -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install timescale/pg-aiguide migrate-postgres-tables-to-hypertables --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/timescale/pg-aiguide.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/migrate-postgres-tables-to-hypertables .agents/skills/migrate-postgres-tables-to-hypertables && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "migrate-postgres-tables-to-hypertables" agent skill from https://github.com/timescale/pg-aiguide/tree/main/skills/migrate-postgres-tables-to-hypertables into .agents/skills/migrate-postgres-tables-to-hypertables/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "migrate-postgres-tables-to-hypertables", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add timescale/pg-aiguide --skill migrate-postgres-tables-to-hypertables -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install timescale/pg-aiguide migrate-postgres-tables-to-hypertables --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/timescale/pg-aiguide.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/migrate-postgres-tables-to-hypertables .cursor/skills/migrate-postgres-tables-to-hypertables && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "migrate-postgres-tables-to-hypertables" agent skill from https://github.com/timescale/pg-aiguide/tree/main/skills/migrate-postgres-tables-to-hypertables into .cursor/skills/migrate-postgres-tables-to-hypertables/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "migrate-postgres-tables-to-hypertables", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/timescale/pg-aiguide.git --path skills/migrate-postgres-tables-to-hypertables--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add timescale/pg-aiguide --skill migrate-postgres-tables-to-hypertables -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install timescale/pg-aiguide migrate-postgres-tables-to-hypertables --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/timescale/pg-aiguide.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/migrate-postgres-tables-to-hypertables .gemini/skills/migrate-postgres-tables-to-hypertables && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "migrate-postgres-tables-to-hypertables" agent skill from https://github.com/timescale/pg-aiguide/tree/main/skills/migrate-postgres-tables-to-hypertables into .gemini/skills/migrate-postgres-tables-to-hypertables/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "migrate-postgres-tables-to-hypertables", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install timescale/pg-aiguide migrate-postgres-tables-to-hypertablesInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add timescale/pg-aiguide --skill migrate-postgres-tables-to-hypertables -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/timescale/pg-aiguide.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/migrate-postgres-tables-to-hypertables .github/skills/migrate-postgres-tables-to-hypertables && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "migrate-postgres-tables-to-hypertables" agent skill from https://github.com/timescale/pg-aiguide/tree/main/skills/migrate-postgres-tables-to-hypertables into .github/skills/migrate-postgres-tables-to-hypertables/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "migrate-postgres-tables-to-hypertables", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add timescale/pg-aiguide --skill migrate-postgres-tables-to-hypertables -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install timescale/pg-aiguide migrate-postgres-tables-to-hypertables --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/timescale/pg-aiguide.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/migrate-postgres-tables-to-hypertables .opencode/skills/migrate-postgres-tables-to-hypertables && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "migrate-postgres-tables-to-hypertables" agent skill from https://github.com/timescale/pg-aiguide/tree/main/skills/migrate-postgres-tables-to-hypertables into .opencode/skills/migrate-postgres-tables-to-hypertables/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "migrate-postgres-tables-to-hypertables", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
migrate-postgres-tables-to-hypertablesA skill your agent uses to migrate identified PostgreSQL tables to Timescale/TimescaleDB hypertables with optimal configuration and validation.
Migrate Postgres Tables To Hypertables is an agent skill from timescale/pg-aiguide. Use this skill to migrate identified PostgreSQL tables to Timescale/TimescaleDB hypertables with optimal configuration and validation. Trigger when user asks to: - Migrate or convert PostgreSQL tables to hypertables - Execute hypertable migration with minimal downtime - Plan blue-green migration for large tables - Validate hypertable migration success - Configure compression after migration Prerequisites: Tables already identified as candidates (use find-hypertable-candidates first if needed) Keywords: migrate to…
Its SKILL.md is about 3.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Requires PostgreSQL 15+ with TimescaleDB
It sits in Databases, covering Deployment. It works with PostgreSQL and Model Context Protocol. The repository describes itself as: MCP server and Claude plugin for Postgres skills and documentation. Helps AI coding tools generate better PostgreSQL code. The licence is Apache-2.0.
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 187be00. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are sql).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Requires PostgreSQL 15+ with TimescaleDB
From compatibility in the SKILL.md frontmatter.
Migrate Postgres Tables To Hypertables loads about 3.8k tokens when it runs. Until then it costs about 233 tokens; SKILL.md has 788 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found patterns that need a careful read before installing.
odify the primary key/unique constraint without user permission.Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from timescale/pg-aiguide at commit 187be00, republished under its Apache-2.0 licence (© timescale). 788 words, ~3,758 tokens.
.claude/skills/migrate-postgres-tables-to-hypertables/SKILL.md (or your agent's skills folder).Migrate identified PostgreSQL tables to TimescaleDB hypertables with optimal configuration, migration planning and validation.
Prerequisites: Tables already identified as hypertable candidates (use companion "find-hypertable-candidates" skill if needed).
-- Find potential partition columns
SELECT column_name, data_type, is_nullable
FROM information_schema.columns
WHERE table_name = 'your_table_name'
AND data_type IN ('timestamp', 'timestamptz', 'bigint', 'integer', 'date')
ORDER BY ordinal_position;Requirements: Time-based (TIMESTAMP/TIMESTAMPTZ/DATE) or sequential integer (INT/BIGINT)
Should represent when the event actually occurred or sequential ordering.
Common choices:
timestamp, created_at, event_time - when event occurredid, sequence_number - auto-increment (for sequential data without timestamps)ingested_at - less ideal, only if primary query dimensionupdated_at - AVOID (records updated out of order, breaks chunk distribution) unless primary query dimensionWhen table has sequential ID (PK) AND timestamp that correlate:
-- Partition by ID, enable minmax sparse indexes on timestamp
SELECT create_hypertable('orders', 'id', chunk_time_interval => 1000000);
ALTER TABLE orders SET (
timescaledb.sparse_index = 'minmax(created_at),...'
);Sparse indexes on time column enable skipping compressed blocks outside queried time ranges.
Use when: ID correlates with time (newer records have higher IDs), need ID-based lookups, time queries also common
-- Ensure statistics are current
ANALYZE your_table_name;
-- Estimate index size per time unit
WITH time_range AS (
SELECT
MIN(timestamp_column) as min_time,
MAX(timestamp_column) as max_time,
EXTRACT(EPOCH FROM (MAX(timestamp_column) - MIN(timestamp_column)))/3600 as total_hours
FROM your_table_name
),
total_index_size AS (
SELECT SUM(pg_relation_size(indexname::regclass)) as total_index_bytes
FROM pg_stat_user_indexes
WHERE schemaname||'.'||tablename = 'your_schema.your_table_name'
)
SELECT
pg_size_pretty(tis.total_index_bytes / tr.total_hours) as index_size_per_hour
FROM time_range tr, total_index_size tis;Target: Indexes of recent chunks < 25% of RAM Default: IMPORTANT: Keep default of 7 days if unsure Range: 1 hour minimum, 30 days maximum
Example: 32GB RAM → target 8GB for recent indexes. If index_size_per_hour = 200MB:
-- Check existing primary key/ unique constraints
SELECT conname, pg_get_constraintdef(oid) as definition
FROM pg_constraint
WHERE conrelid = 'your_table_name'::regclass AND contype = 'p' OR contype = 'u';Rules: PK/UNIQUE must include partition column
Actions:
Example: user prompt if needed:
"Primary key (id) doesn't include partition column (timestamp). Must modify to PRIMARY KEY (id, timestamp) to convert to hypertable. This may break application code. Is this acceptable?" "Unique constraint (id) doesn't include partition column (timestamp). Must modify to UNIQUE (id, timestamp) to convert to hypertable. This may break application code. Is this acceptable?"
If the user accepts, modify the constraint:
BEGIN;
ALTER TABLE your_table_name DROP CONSTRAINT existing_pk_name;
ALTER TABLE your_table_name ADD PRIMARY KEY (existing_columns, partition_column);
COMMIT;If the user does not accept, you should NOT migrate the table.
IMPORTANT: DO NOT modify the primary key/unique constraint without user permission.
For detailed segment_by and order_by selection, see "setup-timescaledb-hypertables" skill. Quick reference:
segment_by: Most common WHERE filter with >100 rows per value per chunk
device_idsymboluser_id or session_id-- Analyze cardinality for segment_by selection
SELECT column_name, COUNT(DISTINCT column_name) as unique_values,
ROUND(COUNT(*)::float / COUNT(DISTINCT column_name), 2) as avg_rows_per_value
FROM your_table_name GROUP BY column_name;order_by: Usually timestamp DESC. The (segment_by, order_by) combination should form a natural time-series progression.
order_by='low_density_col, timestamp DESC'sparse indexes: add minmax on the columns that are used in the WHERE clauses but are not in the segment_by or order_by. Use minmax for columns used in range queries.
ALTER TABLE your_table_name SET (
timescaledb.enable_columnstore,
timescaledb.segmentby = 'entity_id',
timescaledb.orderby = 'timestamp DESC'
timescaledb.sparse_index = 'minmax(value_1),...'
);
-- Compress after data unlikely to change (adjust `after` parameter based on update patterns)
CALL add_columnstore_policy('your_table_name', after => INTERVAL '7 days');-- Enable extension
CREATE EXTENSION IF NOT EXISTS timescaledb;
-- Convert to hypertable (locks table)
SELECT create_hypertable(
'your_table_name',
'timestamp_column',
chunk_time_interval => INTERVAL '7 days',
if_not_exists => TRUE
);
-- Configure compression
ALTER TABLE your_table_name SET (
timescaledb.enable_columnstore,
timescaledb.segmentby = 'entity_id',
timescaledb.orderby = 'timestamp DESC',
timescaledb.sparse_index = 'minmax(value_1),...'
);
-- Adjust `after` parameter based on update patterns
CALL add_columnstore_policy('your_table_name', after => INTERVAL '7 days');-- 1. Create new hypertable
CREATE TABLE your_table_name_new (LIKE your_table_name INCLUDING ALL);
-- 2. Convert to hypertable
SELECT create_hypertable('your_table_name_new', 'timestamp_column');
-- 3. Configure compression
ALTER TABLE your_table_name_new SET (
timescaledb.enable_columnstore,
timescaledb.segmentby = 'entity_id',
timescaledb.orderby = 'timestamp DESC'
);
-- 4. Migrate data in batches
INSERT INTO your_table_name_new
SELECT * FROM your_table_name
WHERE timestamp_column >= '2024-01-01' AND timestamp_column < '2024-02-01';
-- Repeat for each time range
-- 4. Enter maintenance window and do the following:
-- 5. Pause modification of the old table.
-- 6. Copy over the most recent data from the old table to the new table.
-- 7. Swap tables
BEGIN;
ALTER TABLE your_table_name RENAME TO your_table_name_old;
ALTER TABLE your_table_name_new RENAME TO your_table_name;
COMMIT;
-- 8. Exit maintenance window.
-- 9. (sometime much later) Drop old table after validation
-- DROP TABLE your_table_name_old;-- Check foreign keys
SELECT conname, confrelid::regclass as referenced_table
FROM pg_constraint
WHERE (conrelid = 'your_table_name'::regclass
OR confrelid = 'your_table_name'::regclass)
AND contype = 'f';Supported: Plain→Hypertable, Hypertable→Plain NOT supported: Hypertable→Hypertable
⚠️ CRITICAL: Hypertable→Hypertable FKs must be dropped (enforce in application). ASK USER PERMISSION. If no, STOP MIGRATION.
-- Rough estimate: ~75k rows/second
SELECT
pg_size_pretty(pg_total_relation_size(tablename)) as size,
n_live_tup as rows,
ROUND(n_live_tup / 75000.0 / 60, 1) as estimated_minutes
FROM pg_stat_user_tables
WHERE tablename = 'your_table_name';Solutions for large tables (>1GB/10M rows): Use blue-green migration, migrate during off-peak, test on subset first
-- View chunks and compression
SELECT
chunk_name,
pg_size_pretty(total_bytes) as size,
pg_size_pretty(compressed_total_bytes) as compressed_size,
ROUND((total_bytes - compressed_total_bytes::numeric) / total_bytes * 100, 1) as compression_pct,
range_start,
range_end
FROM timescaledb_information.chunks
WHERE hypertable_name = 'your_table_name'
ORDER BY range_start DESC;Look for:
-- 1. Time-range query (should show chunk exclusion)
EXPLAIN (ANALYZE, BUFFERS)
SELECT COUNT(*), AVG(value)
FROM your_table_name
WHERE timestamp >= NOW() - INTERVAL '1 day';
-- 2. Entity + time query (benefits from segment_by)
EXPLAIN (ANALYZE, BUFFERS)
SELECT * FROM your_table_name
WHERE entity_id = 'X' AND timestamp >= NOW() - INTERVAL '1 week';
-- 3. Aggregation (benefits from columnstore)
EXPLAIN (ANALYZE, BUFFERS)
SELECT DATE_TRUNC('hour', timestamp), entity_id, COUNT(*), AVG(value)
FROM your_table_name
WHERE timestamp >= NOW() - INTERVAL '1 month'
GROUP BY 1, 2;✅ Good signs:
❌ Bad signs:
-- Monitor compression effectiveness
SELECT
hypertable_name,
pg_size_pretty(total_bytes) as total_size,
pg_size_pretty(compressed_total_bytes) as compressed_size,
ROUND(compressed_total_bytes::numeric / total_bytes * 100, 1) as compressed_pct_of_total,
ROUND((uncompressed_total_bytes - compressed_total_bytes::numeric) /
uncompressed_total_bytes * 100, 1) as compression_ratio_pct
FROM timescaledb_information.hypertables
WHERE hypertable_name = 'your_table_name';Monitor:
-- Verify chunks are being excluded
EXPLAIN (ANALYZE, BUFFERS)
SELECT * FROM your_table_name
WHERE timestamp >= '2024-01-01' AND timestamp < '2024-01-02';
-- Look for "Chunks excluded during startup: X"-- Get newest compressed chunk name
SELECT chunk_name FROM timescaledb_information.chunks
WHERE hypertable_name = 'your_table_name'
AND compressed_total_bytes IS NOT NULL
ORDER BY range_start DESC LIMIT 1;
-- Analyze segment distribution
SELECT segment_by_column, COUNT(*) as rows_per_segment
FROM _timescaledb_internal._hyper_X_Y_chunk -- Use actual chunk name
GROUP BY 1 ORDER BY 2 DESC;Look for: <20 rows per segment: Poor segment_by choice (should be >100) => Low compression potential.
Check that you don't have too many indexes. Unused indexes hurt insert performance and should be dropped.
SELECT
schemaname,
tablename,
indexname,
idx_tup_read,
idx_tup_fetch,
idx_scan
FROM pg_stat_user_indexes
WHERE tablename LIKE '%your_table_name%'
ORDER BY idx_scan DESC;Look for: Unused indexes via a low idx_scan value. Drop such indexes (but ask user permission).
-- Monitor chunk compression status
CREATE OR REPLACE VIEW hypertable_compression_status AS
SELECT
h.hypertable_name,
COUNT(c.chunk_name) as total_chunks,
COUNT(c.chunk_name) FILTER (WHERE c.compressed_total_bytes IS NOT NULL) as compressed_chunks,
ROUND(
COUNT(c.chunk_name) FILTER (WHERE c.compressed_total_bytes IS NOT NULL)::numeric /
COUNT(c.chunk_name) * 100, 1
) as compression_coverage_pct,
pg_size_pretty(SUM(c.total_bytes)) as total_size,
pg_size_pretty(SUM(c.compressed_total_bytes)) as compressed_size
FROM timescaledb_information.hypertables h
LEFT JOIN timescaledb_information.chunks c ON h.hypertable_name = c.hypertable_name
GROUP BY h.hypertable_name;
-- Query this view regularly to monitor compression progress
SELECT * FROM hypertable_compression_status
WHERE hypertable_name = 'your_table_name';Look for:
✅ Migration successful when:
❌ Investigate if:
Focus on high-volume, insert-heavy workloads with time-based access patterns for best ROI.
© timescale, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/migrate-postgres-tables-to-hypertables of timescale/pg-aiguide.
Open the folder on GitHubat commit 187be00
We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in timescale/pg-aiguide, which our catalogue first saw on October 7, 2026.
Migrate Postgres Tables To Hypertables next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Migrate Postgres Tables To Hypertables this skilltimescale/pg-aiguide | 1.9k | 1 repos | ~3.8k | Automated safety check: Warn | Apache-2.0 | |
| Releasehypequery/hypequery | 103 | — | ~623 | Automated safety check: Pass | Custom licence | |
| Take Doc Screenshotspgplex/pgconsole | 155 | — | ~841 | Automated safety check: Pass | Apache-2.0 | |
| AspireifyCommunityToolkit/Aspire | 629 | — | ~5.3k | Automated safety check: Notes | MIT | |
| Stash Deploymentcipherstash/stack | 157 | — | ~6.5k | Automated safety check: Pass | MIT | |
| Cloudbase CLITencentCloudBase/CloudBase-AI-Toolkit | 1.1k | 1 repos | ~1.7k | Automated safety check: Pass | MIT |
hypequery/hypequery
Cut a stable hypequery release via Changesets, or explain/check the canary flow.
pgplex/pgconsole
Take screenshots of the running pgconsole app for documentation.
CommunityToolkit/Aspire
WORKFLOW SKILL - Wire Aspire AppHosts or repair TypeScript AppHost toolchains.
cipherstash/stack
Deploy a CipherStash encryption rollout to a live environment without losing data — the multi-deploy ladder (schema-add + dual-write → backfill → read cutover → stop dual-writes → drop plaintext)…
TencentCloudBase/CloudBase-AI-Toolkit
CloudBase CLI (tcb, 云开发CLI, Tencent CloudBase命令行) resource management skill.
google/skills
Manages clusters, instances, and backups for AlloyDB for PostgreSQL, and integrates with AlloyDB Model Context Protocol (MCP) tools for automated database operations.
timescale/pg-aiguide
A skill your agent uses to analyze an existing PostgreSQL database and identify which tables should be converted to Timescale/TimescaleDB hypertables.
timescale/pg-aiguide
Explore an existing PostgreSQL database before answering questions about its data or writing SQL.
timescale/pg-aiguide
A skill your agent uses for general PostgreSQL table design.
timescale/pg-aiguide
A skill your agent uses for setting up vector similarity search with pgvector for AI/ML embeddings, RAG applications, or semantic search.
timescale/pg-aiguide
A skill your agent uses to implement hybrid search combining BM25 keyword search with semantic vector search using Reciprocal Rank Fusion (RRF).
timescale/pg-aiguide
A skill your agent uses when creating database schemas or tables for Timescale, TimescaleDB, TigerData, or Tiger Cloud, especially for time-series, IoT, metrics, events, or log data.
Works with
Categories
A skill your agent uses to migrate identified PostgreSQL tables to Timescale/TimescaleDB hypertables with optimal configuration and validation. Migrate Postgres Tables To Hypertables is an agent skill from timescale/pg-aiguide. Use this skill to migrate identified PostgreSQL tables to Timescale/TimescaleDB hypertables with optimal configuration and validation.
Migrate Postgres Tables To Hypertables fits situations like: migrate identified PostgreSQL tables to Timescale/TimescaleDB hypertables with optimal configuration and validation; user asks to: - Migrate; blue-green migration; in-place conversion.
Run `npx skills add timescale/pg-aiguide --skill migrate-postgres-tables-to-hypertables -a claude-code`. Or copy the skill folder (skills/migrate-postgres-tables-to-hypertables in timescale/pg-aiguide) into .claude/skills/migrate-postgres-tables-to-hypertables in your project. Claude Code loads it when a task matches its description.
Run `npx skills add timescale/pg-aiguide --skill migrate-postgres-tables-to-hypertables -a codex`. Or copy the skill folder (skills/migrate-postgres-tables-to-hypertables in timescale/pg-aiguide) into .agents/skills/migrate-postgres-tables-to-hypertables in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add timescale/pg-aiguide --skill migrate-postgres-tables-to-hypertables -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/migrate-postgres-tables-to-hypertables, .gemini/skills/migrate-postgres-tables-to-hypertables, .github/skills/migrate-postgres-tables-to-hypertables and .opencode/skills/migrate-postgres-tables-to-hypertables in your project.
SKILL.md names no scripts, command-line tools or credentials: Migrate Postgres Tables To Hypertables is instructions for the agent only. Compatibility (from SKILL.md): Requires PostgreSQL 15+ with TimescaleDB.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md flagged 1 warning(s): contains instruction-override wording (e.g. “without asking the user”). Read the flagged lines before installing; the check is not a guarantee either way.
Migrate Postgres Tables To Hypertables is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.8k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Migrate Postgres Tables To Hypertables: Release (hypequery/hypequery, 103 stars), Take Doc Screenshots (pgplex/pgconsole, 155 stars), Aspireify (CommunityToolkit/Aspire, 629 stars) and Stash Deployment (cipherstash/stack, 157 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
timescale (a GitHub organization) maintains it in timescale/pg-aiguide, which has 1,862 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on October 7, 2026.
Source: timescale/pg-aiguide on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.