vectorize-io/hindsight is an agent memory system that stores experiences and helps AI agents learn over time instead of only recalling conversation history. It is used by developers adding long-term memory to agents, including coding agents. Catalogue add-ons connect agents to Hindsight and its memory workflows.
Borrowing it
Nothing to install: this file belongs to vectorize-io/hindsight. 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/vectorize-io/hindsight/main/.claude/skills/triage/SKILL.mdgit clone --depth 1 https://github.com/vectorize-io/hindsightWrote 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/vectorize-io/hindsight/triage)<a href="https://agentmods.dev/skills/vectorize-io/hindsight/triage"><img src="https://agentmods.dev/badge/skills/vectorize-io/hindsight/triage/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/vectorize-io/hindsight/triage"><img src="https://agentmods.dev/badge/skills/vectorize-io/hindsight/triage.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 | $0.00079 | $0.01515 |
| Opus 5.5 | $0.00032 | $0.00606 |
| Sonnet 5.5 | $0.00016 | $0.00303 |
| Haiku 4.5 | $0.00008 | $0.00152 |
Grade A, and why
triage 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Triage
Input: a GitHub issue (number or URL) or a problem described in words. Goal: the user knows whether the problem is real, what it does, and what a fix would change — backed by a working POC — and decides before you do the full fix.
Don't do the full fix in this skill. It ends at step 5, with the user's answer.
1. Is it real, and is it a bug?
Read the issue fully (gh issue view <N> --comments): what the reporter saw, what they expected,
version, config. Then check both sides:
- Reproduce it. Find the smallest way to make it happen: a test, a script, an API call. If you can't reproduce it, say so and say what you tried.
- Check whether it's by design. The code shows what happens, not why. Look for the decision:
git log -S '<key string>' --oneline/git log -L/git blameon the lines involved, then read those commits.- The PRs behind them:
gh pr list --state all --search "<keywords>",gh pr view <N> --comments. - Related or duplicate issues:
gh issue list --state all --search "<keywords>". - Hindsight memory, if the plugin is installed (the
hindsight_*tools are available): search the knowledge pages and, when you need the why, run a reflect. Treat what it says as a past record — check it against the code.
2. If it makes no sense, stop here
If it's not real, already fixed, a duplicate, by design, a local setup problem, or not worth changing: tell the user plainly why, with the evidence (commit, PR, issue, line of code). Propose closing it with a short, kind comment, written out ready to post, e.g.:
This is by design: (see #). <What to do instead, if anything.> Closing — feel free to reopen if I missed something.
Ask before posting or closing — never do it on your own.
3. Explore the code
Before writing anything, find what is already there:
- Every caller of the code involved, and every path that can hit the same problem — fix it where they all route through, not only on the path the issue names.
- Similar code that already solves the same kind of problem, and helpers, types and patterns you can
reuse. Read
.claude/skills/code-review/SKILL.mdso the POC already follows the repo's rules. - The tests that cover this area, and how they assert.
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.
- 9d ago First seen · 103 lines · 79 tokens per session scan A c550f93f83ff
triage is a skill published in the GitHub repository vectorize-io/hindsight (55,527 stars, last pushed today), licensed MIT. It adds 79 tokens to every session and 1,515 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-20.
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