Coral is a local application that gives AI agents one SQL interface for querying connected APIs, files, and live data sources. It is for agents and developers who need to retrieve and correlate data across sources while reducing repeated tool calls, pagination, and source-specific integration code. Coral exposes its query interface to compatible agents through MCP, and the catalogue add-ons support using it in agent workflows.
Borrowing it
Nothing to install: this file belongs to withcoral/coral. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/withcoral/coral/main/.agents/skills/retro/SKILL.mdgit clone --depth 1 https://github.com/withcoral/coralWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/withcoral/coral/retro)<a href="https://agentmods.dev/skills/withcoral/coral/retro"><img src="https://agentmods.dev/badge/skills/withcoral/coral/retro/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/withcoral/coral/retro"><img src="https://agentmods.dev/badge/skills/withcoral/coral/retro.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00010 | $0.00953 |
| Opus 5.5 | $0.00004 | $0.00381 |
| Sonnet 5.5 | $0.00002 | $0.00191 |
| Haiku 4.5 | $0.00001 | $0.00095 |
Grade A, and why
retro scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
84% identical to retro — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The user has asked for a retrospective. You are suggesting improvements to the coding agent's environment to improve future runs.
Steps
-
Call the Skill tool with
writing-for-agentsfor the writing style guide. -
Read the primary sources for the session the user specifies. This may mean searching through session logs on this machine. If the user doesn't specify a session, default to the current one.
-
Look for candidates for improvement in these categories.
- Navigation: how easy was it for the agent to find the right files? Are there hidden dependencies between files? Would a navigation pointer make it easier? Use when the session took a long time to find a piece of information.
- Automated checks: are there automated checks that could catch errors the agent made? Linting, typing, tests, filesystem linters? Read the repo's own check command first (its
package.json/build-toollint/checkscripts, its CI workflow), so a check that already exists but sits unwired or silently broken is the finding, not a reinvention. A repo with no guardrail (no pre-commit hook and no CI job running its lint/typecheck/test command) is itself a finding: an un-linted repo is a standing missed opportunity, not a neutral default. Use when the agent made a mistake an automated check could have caught, or the repo has no guardrail at all. - Coding standards: should the reviewer agent be given a new rule to enforce? Should an existing rule be removed or clarified? Classify the violation first: a mechanical one (a fixed syntactic pattern, a banned API, an import shape, a file-location rule) gets a deterministic check, full stop: a custom rule in the repo's own linter, a new pre-commit hook, or a new CI job, whichever the repo's language and existing guardrail make cheapest. Default to building the check over writing the rule. Reserve
CODING_STANDARDS.mdfor genuine judgement calls (cross-file consistency, "matches the surrounding style," anything no guardrail could ever substitute for). Use when the reviewer agent failed to catch a mistake. - Global AGENTS.md: are there any steering instructions that should be moved to coding standards (or automated checks) instead? Use when the AGENTS.md file is particularly large - in the repo OR the user's global scope.
- Tool economy: did the agent make expensive tool calls that could be streamlined? Is there any custom tooling (CLI's, MCP's) that is particularly token-inefficient? Use when the agent made an expensive tool call.
- No-ops: look for instructions in steering files that don't modify the agent's behavior. Use when the steering files are large and unwieldy.
- Information access: look for opportunities to increase the agent's access to information. Teeing dev server logs, readonly access to third-party services. Use when a crucial piece of information was not available to the agent.
- Present these candidates to the user, in order of severity.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 45 lines · 10 tokens per session scan A 33fbc28568e3
retro is a skill published in the GitHub repository withcoral/coral (4,938 stars, last pushed today), licensed Apache-2.0. It adds 10 tokens to every session and 953 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 84% identical to retro, differing in 0 lines, and is treated as a copy.
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